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发表于 2018-2-15 22:13:12 | 显示全部楼层
FightAIDS@home Has a New Tool and a New Teammate
By: Dr. Arthur Olson
Professor, The Scripps Research Institute
9 二月 2018          

Summary
The FightAIDS@Home project is searching for possible compounds to target the protein shell inside HIV (called the capsid core), which protects the viral RNA. Currently, there are no approved drugs that target this protein shell. In this update, Dr. Olson summarizes the team’s progress to-date, describes a new software tool that will help their work, and introduces us to a new research team member.

FAH项有了新的研究工具及团队成员

FAH项目正在寻找一种可靶向于HIV内、保护病毒RNA的蛋白质壳(称为衣壳核心)化合物。目前,尚无批准的药物靶向这种蛋白质壳。在此次更新中,Olson博士总结了团队迄今为止的进展情况,介绍了一种新的软件工具,以帮助他们开展工作,并向我们介绍一位新的研究团队成员。同时,项目先前大部分成果现在都已经收到,我们现在正在实验性地评估30种最有希望的化合物对抗前两个衣壳部位的过程。预计要花大约四个月时间,并重新启动虚拟筛选工作的第一阶段。

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发表于 2018-3-3 08:53:47 | 显示全部楼层
2018-03-01: World Community Grid, Planned Maintenance on Monday, March 5

We are performing database updates on our servers on Monday, March 5 beginning at 18:00 UTC.

---------------
2018.03.01 WCG,计划于3月5日(下周一)进行维护
我们计划在雷锋纪念日对我们的服务器数据库进行一次升级,维护大约在北京时间3月6日凌晨2时(世界协调时 3月5日 18:00)开始

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发表于 2018-3-8 09:42:48 | 显示全部楼层
本帖最后由 0xCAFEBABE 于 2018-3-8 09:46 编辑

Microbiome Immunity Project Already Extending the Known Universe of Protein Structures
By: Tomasz Kosciolek, PhD
UC San Diego Center for Microbiome Innovation
7 三月 2018

摘要
The Microbiome Immunity Project is off to a great start on predicting the structures of hundreds of thousands of bacterial proteins within the human gut. Read about their progress and their plans in their first project update.

Background

The Microbiome Immunity Project was created to better understand the role of the microbiome in intestinal immune response and diseases such as Type 1 Diabetes (T1D) and Inflammatory Bowel Disease (IBD). In this project, we predict structures of bacterial proteins and use this information to annotate their functions and to understand host-microbiome interactions which are responsible for the pathology of IBD and T1D. This is a massive undertaking, as the human gut microbiome has more than 2 million unique proteins, with hundreds of thousands of proteins potentially interacting with human cells. A project of this scale is only possible thanks to the power of World Community Grid.

Our Progress So Far

With your help, we have already predicted the structures of over 50,000 prioritized proteins! In the grand scheme of the 2 million unique bacterial proteins in our gut, this may not seem like a lot, but keep in mind that the experimental work to date covers only approximately 125,000 proteins. In only 6 months we have made tremendous progress by extending our universe of known protein structures by almost 28 percent!

You may have already realized that at this pace, predicting all bacterial protein structures would take years to complete. Fortunately, we don’t have to predict every single structure, because proteins can be grouped into families. These families consist of proteins with similar structures and functions, enabling a comprehensive understanding of the family’s function with only one representative member per family. Once we identify protein families of interest, we will investigate them in more detail.

In the meantime, we have adjusted our strategy on how to prioritize the predictions. Instead of looking only at bacterial genomes (genes of an individual bacterial species), we are investigating bacterial pangenomes (genes of all bacterial strains belonging to the same species). We then prioritize those pangenomes according to their prevalence between individuals in cohort studies investigating the role of microbiome in IBD and T1D. This approach enables us to have the most impact early in the project. We not only have thorough information on microbes involved in T1D and IBD specifically, but we have also expanded our knowledge of the microbiome in general.

We are now extracting information from your predictions, and during the course of the project we plan to make the data available to the public for other exciting research. We are also working on methods to improve predictions of protein functions, enabling us to find the important protein families involved in T1D and IBD among thousands of predictions we have made so far.

All this progress has been made possible thanks to your generous contributions! There is still a lot to discover about the microbiome, but with each computation that you support we are getting a step closer to having a more detailed picture of this important ecosystem inside each of our bodies and understanding IBD and T1D. So, thank you and let’s continue working together on unraveling the mysteries of microbiome!

--------------------

大意:
在您的帮助下,我们已经预测了超过50000个优先蛋白质的结构!在我们肠道中200万种独特的细菌蛋白质的宏大计划中,这似乎并不是很多,但请记住,迄今为止的实验工作只涵盖了大约125000种蛋白质。在短短的6个月内,我们将已知蛋白质结构的范围扩大了近28%,取得了巨大的进展!

您可能已经意识到,按照这个速度,预测所有的细菌蛋白质结构需要数年时间才能完成。幸运的是,我们不必预测每一个结构,因为蛋白质可以分为不同的家族。这些家族由具有相似结构和功能的蛋白质组成,只有每个家族有一名代表成员才能全面了解家族的功能。一旦我们确定了感兴趣的蛋白质家族,我们将更详细地研究它们。

与此同时,我们已经调整了我们的战略,即如何优先考虑预测。而不是只看细菌的基因组(一个细菌物种的基因),我们研究了细菌pangenomes(所有菌株的基因属于同一物种)。然后我们把这些pangenomes根据患病个体之间在队列研究IBD和T1D的微生物的作用。这种方法使我们能够在项目早期发挥最大的影响力。我们不仅详细介绍了T1D和IBD中涉及的微生物,还扩大了对微生物组的了解。

我们现在正在从您的预测中提取信息,并且在项目过程中,我们计划将数据提供给公众进行其他令人兴奋的研究。我们还在研究改进蛋白质功能预测的方法,使我们能够在迄今为止所做的数千次预测中找到涉及T1D和IBD的重要蛋白质家族。

由于您的慷慨捐助使所有这些进展都成为可能!关于微生物群还有很多需要发现的地方,但是在您支持的每一个计算中,我们正在更接近地了解每个人体内这个重要生态系统的细节,并了解IBD和T1D。 所以,谢谢,让我们继续共同努力,揭开微生物组的奥秘!

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发表于 2018-3-21 11:18:09 | 显示全部楼层
本帖最后由 vmzy 于 2018-3-21 11:21 编辑

Drug Search for Leishmaniasis Project Continues Quest for Better Treatments
By: Dr. Carlos Muskus López
Coordinator, Molecular Biology and Computational Unit, PECET University of Antioquia
20 三月 2018         

摘要
The Drug Search for Leishmaniasis researchers recently conducted lab testing on 10 compounds. The testing showed that none of the compounds were good potential treatments, and the researchers will turn their attention to additional compounds.



Sandflies, such as the P. papatasi shown above, are responsible for the spread of leishmaniasis.
Short description of the team’s latest findings

Leishmaniasis is one of the most neglected tropical diseases in the world, infecting more than two million people in 98 countries. The current treatments for all forms of leishmaniasis can cause severe side effects, including death. Furthermore, drug resistant parasites are causing major problems in many countries. For these reasons, there is an urgent need for new, safe, and inexpensive drug compounds.

The Drug Search for Leishmaniasis team has continued their lab testing since their last update. The most recent round of testing involved 10 compounds that had been identified as having potential to be safer, more effective treatments.

The compounds were tested first for toxicity, then for effectiveness against two common parasites that can cause leishmaniasis. Based on the testing, none of the compounds tested would be effective treatments for the disease.

The researchers will make these results public, as they have done with their data to-date. This will alert other scientists to the strong possibility that these particular compounds are not effective against leishmaniasis, and help them make decisions about testing other compounds. Once the team has obtained additional funding, they will test additional compounds that may be useful in treating leishmaniasis.

Anyone interested in a full scientific description of this latest round of testing can read below. Thanks to everyone who supported this project.

In vitro evaluation of the anti-leishmanial activity of predicted molecules by docking

In order to determine if in silico predicted molecules with potential leishmanicidal activity could have the possibility of passing to in vivo assays, the molecules must first pass cytotoxicity testing against human cells in vitro. Then, those molecules that show low or no cytotoxicity are evaluated for parasite growth inhibition in human macrophages and the effective concentration 50 (EC50). The EC50 is the concentration of a molecule that kills 50% of the parasites in vitro.

Evaluation of Cytotoxicity
The cytotoxic activity of the compounds was evaluated on the human cell line U937 (CRL-1593-2 ™ of ATCC). For the evaluations, the cells were used in logarithmic phase of growth and were cultured in 96-well culture plates, at a concentration of 100,000 cells/mL for U937 in RPMI-1640 medium supplemented with 10% fetal bovine serum (SFB) and 1% antibiotics (penicillin-streptomycin) (Sigma). Six serial dilutions prepared from each of the following concentrations: 200 - 100 - 50 - 25.0 and 1 μg / mL were made according to the compound to be evaluated. The cells were incubated at 37°C with 5% CO2 for 72 hours in the presence of the compounds and, subsequently, the effect was determined using the MTT enzyme method. This method uses a dye which live cells metabolize reducing the coloring, which is measured as "Optical Density" (OD).  The plates were incubated at room temperature for another 30 minutes and the formazan production (change of color) was measured at 570 nm in a spectrophotometer. As a control of viability, cells cultured under the same incubation conditions were used in the absence of the compounds. Doxorubicin was used as cytotoxicity control.

The cytotoxicity was determined according to the percentage of decrease in viability and therefore, of the decrease in the number of cells obtained for each compound and doxorubicin, according to the OD values obtained in each experimental condition. The decrease in cell viability, was calculated using the OD values €‹for each condition, i.e., compound or control at the evaluated concentration, using the following equation: % Viability = [OD cells exposed to the compound or control cell / OD cells not exposed] × 100). The values €‹of OD obtained for the cells in the absence of compounds correspond to 100% viability or live cells. Then, with the viability percentages, the mortality percentage was calculated, which corresponds to 100% viability. With the mortality percentages, lethal concentration 50 (LC50) was calculated by the Probit3 program. The cytotoxicity of each compound was classified according to the LC50 values €‹using a proprietary scale: high cytotoxicity LC50 <50 μg/mL; moderate cytotoxicity: 50 < LC50 < 200 μg/mL and low cytotoxicity: LC50> 200 μg/mL.

Table 1 shows the results of cytotoxicity, where it is observed that one compound showed low cytotoxicity while three had moderate cytotoxicity for the U937 human cell line. As expected, doxorubicin, included as a toxicity control, showed high cytotoxicity.



                            Table 1.Evaluation of the in vitro cytotoxicity
Name of Product

CL50 (µg/ml)
X + SD

       Cellular Line U-937            Toxicity Level
ZINC12005520
16.5 ± 0.8                                            High
ZINC16626805
135.7 ± 2.9                                  Moderate
ZINC17135526
12.8 ± 1.8                                            High
ZINC08598759
3.4 ± 0.8                                              High
ZINC32951205
3.7 ± 1.3                                              High
ZINC32951223
27.1 ± 6.1                                            High
ZINC08587552
0.5 ± 0.6                                              High
ZINC08971918
65.6 ± 7.4                                    Moderate
ZINC04777075
>200                                                   Low
ZINC18222288
  53.8 ± 3.0                                    Moderate
Doxorubicin (Control)
0.5 ± 0.1                                              High


Evaluation of Anti-Leishmanial Activity
Prior to the determination of the effective concentration 50 (EC50), all the compounds were pre-selected, by evaluating the effect on the percentage of infection in intracellular amastigotes in the U-937 cell line compared with amastigotes controls, in the absence of the compound.

In this test of leishmanicidal activity in vitro, the fluorescent strains of Leishmania panamensis (UA140-pIR (-) - eGFP) and Leishmania braziliensis (UA301-pIR (-) - eGFP) were used.

The activity of the compounds was evaluated on intracellular parasites (amastigote stage) obtained after in vitro infection of macrophages. The U-937 cells were infected with fluorescent promastigotes in stationary growth phase in a 30:1 parasite:cell ratio for the Leishmania panamensis UA140 strain and 20:1 for Leishmania braziliensis UA301 strain. The infected cells were exposed different concentration of the compounds for 72 hours (see the concentrations used for each compound, in a note below the Table 2).  As infection control, infected cells were used in the absence of the compounds, and amphotericin B was used as a positive control. After 72 hours of incubation, the cells were carefully removed from the bottom of the dish and analyzed in a flow cytometer, reading at 488 nm excitation and 525 nm emission with an Argon4 laser.

The anti-Leishmania activity was determined based on the parasite load, which is the number of parasites in the infected cells exposed to the concentration selected for each compound or amphotericin B. The decrease in parasite load, called inhibition of infection was calculated using the fluorescence mean intensity values €‹(MFI) and using the following formula: % Infection = [MFI cells infected and exposed to the compound or amphotericin B / MFI infected of unexposed cells] × 100). The MFI values ‹obtained for the infected cells in the absence of drug or compound corresponds to 100% of the infection. In turn, the percentage of inhibition of the infection corresponds to 100% of the infection -% infection in the presence of the compound.

Table 2. Evaluation of the percentage of inhibition obtained with the tested compounds in intracellular parasites.
Name of Product
% Inhibition
X + SD

L. panamensis UA140
L. braziliensis UA301
ZINC12005520
19.0 ± 3.0
2.6 ± 0.5
ZINC16626805
0
17.3 ± 6.5
ZINC08598759
12.3 ± 1.9
38.6 ± 1.2
ZINC32951205
8.0 ± 0.9
29.4 ± 6.6
ZINC32951223
1.2 ± 0.4
0
ZINC08587552
6.6 ± 3.3
0.3 ± 0.5
ZINC08971918
0
3.0 ± 5.9
ZINC04777075
0
33.4 ± 4.2
ZINC18222288
0
14.3 ± 5.0
Amphotericin B-Control
75.9 ± 5.5
71.6 ± 5.1


The EC50 was not determined for any of the molecules, because none of the compounds showed an inhibition percentage greater than 50% in the two Leishmania species used (See Table 2).

Conclusion
None of the 10 molecules evaluated showed promising anti-leishmanial results based on the in vitro cytotoxicity inhibition assays. And given this, the EC50 was not evaluated.
大意:
DSFL对项目筛选出的10个潜在分子进行了实验室测试,全军覆没。

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发表于 2018-3-30 15:03:54 | 显示全部楼层
By: Dr. Anna Croft
University of Nottingham, UK
29 三月 2018          

摘要
The Help Stop TB researchers are looking to expand their team as they analyze the large amount of data generated by World Community Grid. Read about their plans in this update.


Dr. Athina Meletiou (pictured above speaking about the Help Stop TB project) recently completed her PhD and has begun a new position. We wish her the best of luck, and thank her for her work on the project.

Background

Tuberculosis remains one the world’s major killers from infectious disease. The World Health Organization announced in a recent report that 6.3 million new cases of TB were reported in 2016, up from 6.1 million in 2015.

Tuberculosis can be difficult to treat because the bacterium which causes the disease has an unusual coating which protects it from many drugs and from a person’s immune system. Among the fats, sugars and proteins in this coat, the TB bacterium contains a type of fatty molecules called mycolic acids. The Help Stop TB (HSTB) project simulates the behavior of these molecules to better understand how they offer protection to the TB bacteria. With the resulting information, scientists may be able to design better ways to attack this protective layer and therefore develop better treatments for this deadly disease.

Congratulations and Changes

Since our last update, we’ve been undergoing further changes to the project team.

Athina Meletiou is now Dr. Athina Meletiou, having successfully passed her PhD viva (oral examination). She has taken up an EU-funded postdoctoral fellowship working on another large data project of one of our colleagues at University of Nottingham, Professor Charles Laughton, “Advanced multiscale simulation of DNA.”

Athina will still be touching base, as we will be preparing publications from her work in the near future. In the meantime, we wish her well with her next step in her career, with many thanks for the hard work she has put into the HSTB project to grow it into the success it has been so far.

The Search for New Team Members

As a result of Athina’s move, we are now actively looking for new team members, especially those with a strong interest in data science, as we now have a significant quantity of data to mine, for which we would love to apply new approaches. We also want to tackle the development of accurate membrane models, now that we have sufficient atomistic data. Applications from suitably qualified chemists, biochemists, mathematicians, engineers, and computer scientists are welcomed, both for PhD-level and postdoctoral posts.

Our opportunities include a BBSRC-funded PhD studentship available to UK/EU applicants (with applications for 2019 start to open later this year), and we have the possibility to support exceptionally talented potential students through our local PhD scholarships scheme for a start this year.

We are also happy to help support qualified applicants through our fellowships processes--these include applications for the prestigious EU-funded Marie Skłodowska-Curie fellowships, and local Nottingham Research fellowships or Anne-McLaren fellowships (see our website for details) alongside those from the learned societies.

If you have the drive and the skills to join us, please get in touch.


--------------------

背景:

结核病仍然是世界传染病的主要杀手之一。世界卫生组织在最近的一份报告中宣布2016年新增630万例TB,比2015年的610万增加。

结核病可能难以治疗,因为导致疾病的细菌有一种不寻常的涂层,可以保护它免受许多药物和人体免疫系统的伤害。
在这种脂肪中,糖和蛋白质作为外壳,TB细菌含有一种称为分枝菌酸的脂肪分子。
帮助遏制结核病(HSTB)项目模拟这些分子的行为,以更好地了解它们如何为结核菌提供保护。
有了这些信息,科学家们可以设计出更好的方法来攻击这种保护层,从而为这种致命的疾病开发更好的治疗方法。


大意:

由于 Athina Meletiou 博士跳槽了,我们需要寻找新的团队成员,尤其是那些对数据科学有浓厚兴趣的团队成员。
欢迎来自化学家,生物化学家,数学家,工程师和计算机科学家的申请,无论是博士还是博士后。

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发表于 2018-4-27 11:57:46 | 显示全部楼层
Announcing Three Winning Climate Change Projects
26 四月 2018         

摘要
After a rigorous review of dozens of applications from all over the world, we're excited to announce the research groups who will receive supercomputing power, weather data, and cloud storage from IBM to accelerate climate change science.



As our planet faces the mounting impacts of climate change, scientists are on the front lines of understanding complex consequences and developing solutions.

We've heard from climate change scientists that common bottlenecks they face include limited access to weather data, and insufficient computing power and data storage capacity to accurately simulate the impacts of climate change.

These are some of the reasons why IBM Corporate Citizenship recently invited scientists to apply for grants of massive computing power from World Community Grid, meteorological data from The Weather Company, and data storage from IBM Cloud Object Storage to support their climate change or environmental research projects. (More information about these IBM resources can be found here.)

As a result of this call for proposals, we received more than 70 responses from researchers all over the world. We're thrilled to announce the winners of these resources:

Impact of climate change on public health (Emory University, USA)
This project will examine the impact of climate change on temperature and air pollution at local levels, helping researchers understand the impact of a changing climate on human health.

Impact of atmospheric aerosols on climate change (Far Eastern Federal University, Russia)
Atmospheric aerosols, such as dust, smoke and pollution, both absorb and reflect sunlight in the atmosphere, and represent the greatest area of uncertainty in climate science today, according to the UN Intergovernmental Panel on Climate Change (IPCC). This project aims to determine how super-micron particles (6 to 12 micrometers in diameter) interact with sunlight and how they contribute to atmospheric temperatures--information that will improve the accuracy of climate models.

Rainfall modeling in Africa (Delft University of Technology, Netherlands)
In Africa, agriculture relies heavily on localized rainfall, which is difficult to predict. In collaboration with the Trans-African Hydro-Meteorological Observatory, which aims to develop a vast network of weather stations across Africa, researchers will simulate rainfall on the continent. Such information could help farmers be more resilient, among other weather and hydrology applications.


These proposals were evaluated by IBM scientists and an outside team of experts for scientific merit, potential to contribute to the global community's understanding of specific climate and environmental challenges, and the capacity of the research team to manage a sustained research project. Researchers also agreed, if they received these resources, to abide by our open data policy by publicly releasing the data from their collaboration with us.

In the coming months, we'll be updating everyone as we get ready to launch these projects. In the meantime, current World Community Grid volunteers who want to support these projects as soon as they start can go to the My Projects page to opt in to new projects as they become available.

If you’re not yet a World Community Grid volunteer, you can sign up to be notified as soon as the first of these three projects is launched. You can also join World Community Grid right now and support our existing projects.

Thanks to everyone for your support and stay tuned for further news!
大意:
审核通过了三个新的气候类项目,接下来几个月会逐步上线。

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发表于 2018-5-23 09:29:52 | 显示全部楼层

FightAIDS@Home – Phase 2 Prepares for A New Stage

本帖最后由 0xCAFEBABE 于 2018-5-23 09:39 编辑

By: The FightAIDS@home research team
22 五月 2018         

摘要
The FightAIDS@Home – Phase 2 researchers are making plans to write a paper and to test new compounds as part of the continuing search for new and better treatments.

Background

Researchers all over the world have been making advances in the battle against HIV/AIDS for many years. However, AIDS-related complications still affect far too many people. UNAIDS estimates that 36.7 million people were living with HIV in 2016. And while AIDS-related deaths have decreased significantly since their peak in 2005, approximately 1 million people died of causes related to AIDS in 2016. (See the UNAIDS website for more statistics.)

HIV continues to be a challenge because it quickly mutates in ways that make existing drug treatments ineffective. FightAIDS@Home joined World Community Grid more than a decade ago with the simple but challenging goal of finding new treatments for HIV. During Phase 1 of the project, the team identified thousands of potentially promising candidates to be confirmed experimentally in the lab. However, because it’s cost and time prohibitive to lab test all the potential candidates, Phase 2 was created to prioritize the candidate compounds by evaluating them with more accurate methods.

Current Work

Our team is processing the current type of work units through World Community Grid as quickly as possible. Once these work units are completed, we plan to write a paper about the process, including its strengths, limitations, and lessons learned.

We are also planning to use World Community Grid’s computing power to analyze new compounds that are important to our work with the HIVE Center at the Scripps Research Institute. This work will begin after we run a sample of these new compounds on our own grid computing network.

Thank You

We appreciate everyone who continues to donate their computing power to the search for better anti-HIV treatments. We also encourage everyone to opt in to Phase 2 of the project—the more quickly we can run through the current work units, the sooner we can move ahead to new compounds.
----------------------------------------------------------------------

大意:
我们将通过WCG尽快处理完当前的工作,并将处理过程撰写成论文,包括其优势,局限性和经验教训。
我们还计划利用WCG的计算能力来分析对我们与斯克里普斯(Scripps)研究所HIVE中心合作研究的非常重要的新化合物。
这项工作将在我们自己的网格计算网络上运行这些新化合物的样本后开始。

致谢:
我们感谢每一个继续捐赠他们的计算能力的人,以寻求更好的抗HIV治疗。 我们也鼓励大家选择进入项目的第二阶段 - 帮助我们可以更快地完成目前的工作,使我们可以更早的进入新化合物阶段的研究。

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发表于 2018-6-1 09:10:28 | 显示全部楼层

Planned Maintenance on Monday, June 4

31 五月 2018         

摘要
We are updating the operating system on our servers on Monday, June 4, beginning at 15:00 UTC.

We will be applying an important operating system update to our servers on Monday, June 4, beginning at 15:00 UTC. We anticipate that the work will take approximately four hours.

During this time, volunteers will not be able to upload or download new work, and the website will not be accessible. No action is required by you, as your devices will automatically retry their connections after the maintenance work is completed.

We appreciate your patience and participation.



大意:
计划在 2018年6月4日15:00UTC - 19:00UTC(北京时间2018/6/4 23:00 - 2018/6/5 03:00)给服务器的操作系统打补丁。
维护期间客户端无法上传或下载任务,维护完成后服务会自动恢复,不需要捐赠者做任何操作。
感谢支持。
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发表于 2018-6-6 14:44:51 | 显示全部楼层

Smash Childhood Cancer Researchers Choose New Target Molecules

By: Dr. Akira Nakagawara, MD, PhD
CEO of the Saga Medical Center KOSEIKAN and President Emeritus, Chiba Cancer Center
5 六月 2018

摘要
The Smash Childhood Cancer research team recently chose several new target molecules as the focus of their current work. Learn more about the significance of these molecules in this update.

Almost a year and a half has passed since we kicked off the Smash Childhood Cancer project. On behalf of all the team members, I really appreciate volunteers' contributions to this project.

By adding new members to the original group from the Help Fight Childhood Cancer project, our research team for Smash Childhood Cancer has become quite international, with pediatricians from Japan, Hong Kong, and the United States involved in this big, new drug development project.

While the Help Fight Childhood Cancer project's goal was to search for new and better treatments for neuroblastoma, Smash Childhood Cancer addresses not only neuroblastoma, but other childhood cancers such as brain tumors, osteosarcoma (bone cancer), germ cell tumors, hepatoblastoma (liver cancer), and others.

Several proteins--beta-catenin, LIN28B , N-CYM and others--have been newly chosen as target molecules. The structures of the beta-catenin and LIN28B proteins have been determined, so in silico screening for these has been started, looking for high binding affinity compounds from a library of more than 3 million small molecules.

The N-CYM protein, which was discovered by my team and myself, is the novel driving gene product of neuroblastoma. The protein is only found in humans and chimpanzees, and is created through de novo evolution (meaning it is part of the evolution of the cancer). The protein is quite difficult to crystallize for some reason and we are still working on determining its exact structure so that drug discovery against it could begin.

Recently, we received a grant from Japanese government to support our drug discovery against the LIN28B protein, which may help accelerate our progress on Smash Childhood Cancer.

Once again, I would like to express our gratitude for volunteers all over the world who have been supporting the project. For children who are fighting childhood cancer, we would like to discover a new drug as soon as possible and develop a treatment without subsequent side effects.

======================================

机翻:

儿童癌症研究小组最近选择了几个新的靶分子作为他们当前工作的重点。了解更多关于这些分子在这次更新中的意义。

自从我们开始 SCC 项目以来,将近一年半的时间过去了。我代表所有的团队成员,非常感谢志愿者对这个项目的贡献。

我们 SCC 的项目已经相当国际化,团队中加入了来自日本、香港儿科医生和美国的成员参与新药研发的项目。

虽然 SCC 项目的目标是寻找新的和更好的神经母细胞瘤治疗方法,粉碎儿童癌症不仅涉及神经母细胞瘤,还包括其他儿童癌症,如脑肿瘤、骨肉瘤(骨癌)、生殖细胞肿瘤、肝母细胞瘤(肝癌),以及其他。

β-连环蛋白、Ln8B、N-CYM等蛋白质已被新选择为目标分子。β-连环蛋白和Len8B蛋白的结构已被确定,因此在硅片上对这些进行了筛选,从300万个小分子库中寻找高结合亲和力化合物。

Ni-Cym蛋白是我和我团队发现的神经母细胞瘤新的驱动基因产物。这种蛋白质只存在于人类和黑猩猩中,是通过从头进化而产生的(这意味着它是癌症进化的一部分)。由于某种原因,这种蛋白质很难结晶,我们仍在努力确定其确切的结构,从而开始研发对抗它的药物。

最近,我们收到了来自日本政府的资助,以支持我们的药物发现对LI28 B蛋白,这将有助于加速 SCC 项目的进展。

再一次,我要向全世界的志愿者们表达我们的感激之情。对于那些正在抗击儿童癌症的儿童,我们希望尽快发现一种新药,并开发一种无副作用的治疗方法。

======================================

大意:
团队中新加入了来自日本、香港儿科医生和美国的成员参与新药研发的项目。
最近的工作重点是选择了几个新的靶向分子进行研究。
非常感谢志愿者对项目的贡献。
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发表于 2018-6-13 09:25:03 | 显示全部楼层
Planned Maintenance on Thursday, June 14
12 六月 2018         

摘要
We are updating the storage system on our servers on Thursday, June 14, beginning at 15:00 UTC.

We will be applying an important storage system update to our servers on Thursday, June 14, beginning at 15:00 UTC. We anticipate that the work will take approximately four hours.

During this time, volunteers will not be able to upload or download new work. No action is required by you, as your devices will automatically retry their connections after the maintenance work is completed.

We appreciate your patience and participation.大意:
计划于北京时间6月14号(周四)晚23点对存储系统进行升级,大概耗时4个小时。届时将暂停任务上传/下载。
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发表于 2018-6-26 09:43:31 | 显示全部楼层
Planned Maintenance on Tuesday, June 26
25 六月 2018          

摘要
We are updating the operating system on our servers on Tuesday, June 26, beginning at 18:00 UTC.

We will be applying an important operating system update to our servers on Tuesday, June 26, beginning at 18:00 UTC. We anticipate that the work will take approximately four hours.

During this time, volunteers will not be able to upload or download new work, and the World Community Grid website will not be accessible. No action is required by you, as your devices will automatically retry their connections after the maintenance work is completed.

We appreciate your patience and participation.
大意:
计划于北京时间6月27号(周三)凌晨2点对操作系统进行升级,预计耗时4小时左右,届时全站下线。
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发表于 2018-7-6 09:07:34 | 显示全部楼层
Planned Maintenance on Tuesday, July 10  
5 七月 2018          

摘要
We are updating the operating system on our servers on Tuesday, July 10, beginning at 14:00 UTC.

We will be applying an important operating system update to our servers on Tuesday, July 10, beginning at 14:00 UTC. We anticipate that the work will take approximately four hours.

During this time, volunteers will not be able to upload or download new work, and the World Community Grid website will not be accessible. No action is required by you, as your devices will automatically retry their connections after the maintenance work is completed.

We appreciate your patience and participation.
大意:
计划于北京时间7月10号(周二)晚22点对操作系统进行升级,预计耗时4小时左右,届时全站下线。
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发表于 2018-8-9 10:07:08 | 显示全部楼层
本帖最后由 0xCAFEBABE 于 2018-8-9 21:56 编辑

Sarcoma Dataset Coming Soon to Mapping Cancer Markers Project
By: Dr. Igor Jurisica
Krembil Research Institute, University Health Network, Toronto
8 八月 2018         

----------
原文及机翻
----------

摘要
In this comprehensive update, the Mapping Cancer Markers team explains how they are determining which genes and gene signatures carry the greatest promise for lung cancer diagnosis. They also introduce the next type of cancer--sarcoma--to be added soon to the project.

在这一全面更新中,映射癌症标记团队解释了他们是如何确定哪些基因和基因签名对肺癌诊断具有最大的希望。他们还介绍了下一种癌症——肉瘤——即将加入该项目。

The Mapping Cancer Markers (MCM) project continues to process work units for the ovarian cancer dataset. As we accumulate these outcomes, we continue to analyze MCM results from the lung cancer dataset. In this update, we discuss preliminary findings from this analysis. In addition, we introduce the sarcoma dataset that will be our focus in the next stage.

映射癌症标记物(MCM)项目继续处理卵巢癌数据集的工作单位。当我们积累这些结果时,我们继续分析肺癌数据集的MCM结果。在本次更新中,我们将讨论初步分析结果。此外,我们介绍了肉瘤数据集,将是我们在下一个阶段的重点。

Patterns of gene-family biomarkers in lung cancer

肺癌基因家族生物标志物的模式

In cancer, and human biology in general, multiple groups of biomarkers (genes, protein, microRNAs, etc.) can have similar patterns of activity and thus clinical utility, helping diagnosis, prognosis or predicting treatment outcome. For each cancer subtype, one could find large number of such groups of biomarkers, each having similar predictive power; yet current statistical and AI-based methods identify only one from a given data set.

在癌症和人类生物学中,多组生物标志物(基因、蛋白质、microRNA等)可以具有类似的活动模式,从而具有临床实用性,有助于诊断、预后或预测治疗结果。对于每个癌症亚型,人们可以发现大量这样的生物标志物,每个都具有相似的预测能力;然而,目前的统计和基于人工智能的方法仅从给定的数据集中识别出一个。

We have two primary goals in MCM: 1) to find good groups of biomarkers for the cancers we study, and 2) to identify how and why these biomarkers form useful groups, so we can build a heuristic approach that will find such groups for any disease without needing months of computation on World Community Grid. The first goal will give us not only information that after validation may be useful in clinical practice, but importantly, it will generate data that we will use to validate our heuristics.

我们在MCM中有两个主要目标:1)寻找我们研究的癌症的良好生物标记组,和2)识别这些生物标记如何以及为什么形成有用的组,因此我们可以构建一种启发式方法,可以在不需要数个月的世界通信计算的情况下为任何疾病找到这样的组。TY网格。第一个目标将不仅给我们信息,验证后可能是有用的在临床实践中,但重要的是,它将产生的数据,我们将用于验证我们的启发式。


Illustration 1: Proteins group by similar interactions and similar biological functions.
图解1:蛋白质组由相似的相互作用和相似的生物学功能组成。

Multiple groups of biomarkers exist primarily due to the redundancy and complex wiring of the biological system. For example, the highly interconnected human protein-protein interaction network enables us to see how individual proteins perform diverse molecular functions and together contribute to a specific biological process, as shown above in Illustration 1. Many of these interactions change between healthy and disease states, which in turn affects the functions these proteins carry. Through these analyses, we aim to build models of these processes that in turn could be used to design new therapeutic approaches.

多组生物标记物的存在主要是由于生物系统的冗余和复杂的布线。例如,高度相互连接的人蛋白-蛋白质相互作用网络使我们能够看到个体蛋白质如何执行不同的分子功能并共同促成特定的生物过程,如上文在图1中所示。许多这些相互作用在健康状态和疾病状态之间变化,进而影响这些蛋白质携带的功能。通过这些分析,我们的目标是建立这些过程的模型,进而可以用来设计新的治疗方法。

Two specific groups of biomarkers may appear different from each other, yet perform equivalently because the proteins perform similar molecular functions. However, using these groups of biomarkers for patient stratification may not be straightforward. Groups of biomarkers often do not validate in new patient cohorts or when measured by different biological assays, and there are thousands of possible combinations to consider. Some groups of biomarkers may have all reagents available while others may need to be develop (or be more expensive); they may also have different robustness, sensitivity and accuracy, affecting their potential as clinically useful biomarkers.

生物标志物的两个特定基团可能会出现彼此不同,但等效地执行,因为蛋白质执行类似的分子功能。然而,使用这些生物标志物对患者分层可能并不简单。生物标志物的组通常不验证在新的患者队列中或当通过不同的生物测定来测量,并且有成千上万种可能的组合要考虑。一些生物标志物可能有所有试剂可用,而其他一些可能需要开发(或更昂贵);它们也可能具有不同的健壮性、敏感性和准确性,影响它们作为临床有用生物标志物的潜力。

At the present time, there is no effective approach to find all good groups of biomarkers necessary to achieve the defined goal, such as accurately predicting patient risk or response to treatment.

目前,还没有有效的方法来找到所有必要的生物标志物来实现所定义的目标,例如准确预测患者的风险或对治疗的反应。

The first goal of the Mapping Cancer Markers project is to gain a deeper understanding of the “rules” of why and how proteins interact and can be combined to form a group of biomarkers, which is essential to understanding their role and applicability. Therefore, we are using the unique computational resource of World Community Grid to systematically survey the landscape of useful groups of biomarkers for multiple cancers and purposes (diagnosis and prognosis). Thereby, we established a benchmark for cancer gene biomarker identification and validation. Simultaneously, we are applying unsupervised learning methods such as hierarchical clustering to proteins that group by predictive power and biological function.

癌症标记物项目的第一个目标是深入了解蛋白质相互作用的原因和规律,并将它们组合起来形成一组生物标记物,这对于了解它们的作用和适用性是至关重要的。因此,我们利用世界社区网格的独特计算资源,系统地调查多种癌症和目的(诊断和预后)的有用生物标记群的景观。因此,我们建立了一个癌症基因标志物鉴定和验证的基准。同时,我们采用无监督学习方法,如分层聚类的蛋白质组的预测能力和生物功能。

The combination of this clustering and the World Community Grid patterns enables us to identify generalized gene clusters that provide deeper insights to the molecular background of cancers, and give rise to more reliable groups of gene biomarkers for cancer detection and prognosis.

这种集群和世界社区网格模式的结合使我们能够识别广义的基因簇,从而为癌症的分子背景提供更深入的见解,并为癌症检测和预后提供更可靠的基因生物标记组。

Currently, we are focusing on the first-phase results from the lung cancer dataset, which focused on a systematic exploration of the entire space of potential fixed-length groups of biomarkers.

目前,我们关注的是肺癌数据集的第一阶段结果,其重点是对潜在固定长度的生物标志物的整个空间的系统探索。


Illustration 2: Workflow of the MCM-gene-pattern-family search. The results of the World Community Grid analysis combined with the unsupervised clustering of genes identifies a set of gene-pattern-families, generalizing the groups of biomarkers. Finally, the results are evaluated using known cancer biomarkers and by using functional annotations, such as signaling pathways, gene ontology function and processes.
说明2:MCM基因模式家族搜索的流程。世界社区网格分析与基因的无监督聚类结合的结果识别了一组基因模式家族,概括了生物标志物的组。最后,使用已知的癌症生物标志物和使用功能注释,如信号通路、基因本体功能和过程来评价结果。

As depicted above in Illustration 2, World Community Grid computed about 10 billion randomly selected groups of biomarkers, to help us understand the distribution of which group sizes and biomarker combinations perform well, which in turn we will use to validate heuristic approaches. Analysis showed that about 45 million groups of biomarkers had a high predictive power and passed the quality threshold. This evaluation gives us a detailed and systematic picture of which genes and gene groups carry the most valuable information for lung cancer diagnosis. Adding pathway and protein interaction network data enables us to further interpret and fathom how and why these groups of biomarkers perform well, and what processes and functions these proteins carry.

如图2所示,世界社区网格计算了100亿个随机选择的生物标记组,以帮助我们了解哪些组大小和生物标记组合的分布表现良好,这反过来我们将用于验证启发式方法。分析表明,约4500万组生物标志物具有较高的预测能力,并通过了质量阈值。这个评价给我们一个详细和系统的图片,哪些基因和基因组携带最有价值的信息为肺癌诊断。添加途径和蛋白质相互作用网络数据使我们能够进一步解释和揣测这些生物标记物如何以及为什么表现良好,以及这些蛋白质携带哪些过程和功能。

Simultaneously, we used the described lung cancer data to discover groups of similar genes. We assume that these genes or the encoded proteins fulfill similar biological functions or are involved in the same molecular processes.

同时,我们使用所描述的肺癌数据来发现相似基因的组。我们假设这些基因或编码的蛋白质实现相似的生物学功能或参与相同的分子过程。


Illustration 3: Evaluation of the hierarchical clustering of the lung cancer data, using the complete linkage parameter, for different numbers of groups indicated by the K-values (100 to 1000). The first plot shows the silhouette value - a quality metric in this clustering, i.e., measure of how well each object relates to its cluster compared to other clusters. The second plot depicts the inter- and intra-cluster distance and the ratio of intra/inter cluster distance.
说明3:使用完整的连锁参数对K值(100至1000)所指示的不同数目的组的肺癌数据的分级聚类进行评价。第一个情节显示剪影值-在这个聚类中的质量度量,即,衡量每个对象相对于它的集群与其他集群相比有多好。第二个图描绘了簇内距离和簇内距离以及簇内/簇间距离的比率。

To find the appropriate clustering algorithms and the right number of gene groups (clusters) we use different measures to evaluate the quality of each of the individual clustering. For instance, Illustration 3 (above) shows the results of the evaluation of the hierarchical clustering for different numbers of clusters. To evaluate clustering quality, we used silhouette value (method for assessing consistency within clusters of data, i.e., measure of how well each object relates to its own cluster compared to other clusters). A high silhouette value indicates good clustering configuration, and the figure shows a large increase in the silhouette value at 700 gene groups. Since this indicates a significant increase in quality, we subsequently select this clustering for further analysis.

为了找到合适的聚类算法和正确数量的基因群(簇),我们使用不同的措施来评估每个个体聚类的质量。例如,图解3(上文)示出了对于不同数量的簇的层次聚类的评价结果。为了评估聚类质量,我们使用轮廓值(用于评估数据簇内的一致性的方法,即,衡量每个对象相对于它自己的集群与其他集群相比有多好)。一个高的轮廓值表明良好的聚类配置,并且图显示在700个基因组中剪影值的大幅增加。由于这表明质量的显著提高,我们随后选择这种聚类进行进一步的分析。

Not all combinations of biological functions or the lack of it will lead to cancer development and will be biologically important. In the next step, we apply a statistical search to investigate which combinations of clusters are most common among the well-preforming biomarkers, and therefore result in gene groups or pattern families. Since some gene-pattern-families are likely to occur even at random, we use enrichment analysis to ensure the selection only contains families that occur significantly more often than random.

不是所有生物功能的组合或缺乏它都会导致癌症的发展,并且在生物学上是重要的。在下一个步骤中,我们应用统计搜索来研究哪些簇合物在预形成的生物标志物中最常见,从而导致基因组或模式家族。由于一些基因模式家族甚至可能随机出现,所以我们使用富集分析来确保选择只包含显著多于随机发生的家庭。

In the subsequent step we validated the selected generalized gene-pattern-families using an independent set of 28 lung cancer data sets. Each of these studies report one or several groups of biomarkers of up- or down-regulated genes that are indicative for lung cancer.

在随后的步骤中,我们使用一组独立的28个肺癌数据集验证选定的广义基因模式家族。这些研究报告了一种或几组生物标志物,它们是肺癌的上调或下调基因。


Illustration 4: Shown is a selection of high performing pattern families and how they are supported by 28 previously published gene signatures. Each circle in the figure indicates the strength of the support: The size of the circle represents the number of clusters in the family that where found significantly more often in the signature of this study. The color of the circle indicates the average significance calculated for all clusters in the pattern-family.
插图4:示出了高性能模式家族的选择以及它们如何被28个先前公布的基因签名所支持。图中的每个圆表示支持的强度:圆的大小代表家庭中的簇的数目,在这项研究的签名中发现了更多的簇。圆的颜色表示模式族中所有簇计算的平均值。

Illustration 4 depicts a selection of the most prevalent pattern families and the studies that support them. Each circle in the figure indicates the strength of the support: The size of the circle represents the number of clusters in the family that where found significantly more often in the biomarker of this study. The color of the circle indicates the average significance calculated for all clusters in the pattern-family.

插图4:示出了高性能模式家族的选择以及它们如何被28个先前公布的基因签名所支持。图中的每个圆表示支持的强度:圆的大小代表家庭中的簇的数目,在这项研究的签名中发现了更多的簇。圆的颜色表示模式族中所有簇计算的平均值。


Illustration 5: One of the most frequent gene-pattern-families, is a combination of cluster 1, 7 and 21. We annotated each cluster with pathways using pathDIP and visualized it using word clouds (the larger the word/phrase, the most frequently it occurs).
插图5:最常见的基因模式家族之一,是簇1, 7和21的组合。我们用PATDIP注释每个簇的路径,并用词云可视化它(单词/短语越大,出现的频率越大)。

Finally, we annotated the most effective gene-pattern-families and their gene clusters with molecular functions and pathways that the genes or corresponding proteins are involved in. Illustration 5 shows an example for such a gene-pattern-family that comprises gene-clusters 7, 1 and 21.

最后,我们用基因或相应的蛋白参与的分子功能和途径来注释最有效的基因型家族及其基因簇。图解5示出了包括基因簇7, 1和21的这样的基因模式家族的示例。

The word cloud visualization indicates that cluster 7 is involved in pathways related to GPCRs (G protein–coupled receptor) and NHRs (nuclear hormone receptors). In contrast, the genes in cluster 1 are highly enriched in EGFR1 (epidermal growth factor receptor) as well as translational regulation pathways. Mutations affecting the expression of EGFR1, a transmembrane protein, have shown to result in different types of cancer, and in particular lung cancer (as we have shown earlier, e.g., (Petschnigg et al., J Mol Biol 2017; Petschnigg et al., Nat Methods 2014)). The aberrations increase the kinase activity of EGFR1, leading to hyperactivation of downstream pro-survival signaling pathways and a subsequent uncontrolled cell division. The discovery of EGFR1 initiated the development of therapeutic approaches against various cancer types including lung cancer. The third group of genes are common targets of microRNAs. Cluster 21 indicates strong involvement with microRNAs, as we and others have shown before (Tokar et al., Oncotarget 2018; Becker-Santos et al., J Pathology, 2016; Cinegaglia et al., Oncotarget 2016).

云可视化表明,簇7参与了与GPCRs(G蛋白偶联受体)和NHRs(核激素受体)相关的通路。相反,簇1中的基因高度富集EGFR1(表皮生长因子受体)和翻译调控途径。影响EGFR1,跨膜蛋白的表达的突变已经显示出不同类型的癌症,特别是肺癌(如我们先前所示,例如,(Pet Snigigg等人,J.mol BioL 2017;PeStHigigg等人,NAT方法2014))。畸变增加EGFR1的激酶活性,导致下游的促存活信号通路的过度激活和随后的不受控制的细胞分裂。EGFR1的发现引发了针对各种癌症类型的治疗方法的发展,包括肺癌。第三组基因是microRNA的共同靶点。集群21表明与microRNA的强烈参与,正如我们和其他人之前所展示的(Tokar等人,OnCo Talk 2018;Becker Santos等人,J病理学,2016;CieGigaLa等人,OnCo Talk 2016)。


Illustration 6: Evaluation of enriched pathways for cluster 1. Here we used our publicly available pathway enrichment analysis portal pathDIP (Rahmati et al., NAR 2017). The network was generated with our network visualization and analysis tool NAViGaTOR 3 (http://ophid.utoronto.ca/navigator).
图解6:簇1的富集途径的评价。在这里,我们使用我们的公开途径富集分析门户PATDIP(RaMaTaI等人,NAR 2017)。该网络是由我们的网络可视化和分析工具 NAViGaTOR 3 生成的。

The final illustration evaluates the 20 most significantly enriched pathways for cluster 1. The size of the pathway nodes corresponds to the number of involved genes, and the width of the edges corresponds the number genes of overlapping between pathways. One can see that all pathways involved in translation are highly overlapping. mRNA-related pathways form another highly connected component in the graph. The EGFR1 pathway is strongly overlapping with many of the other pathways, indicating that genes that are affected by those pathways are involved in a similar molecular mechanism.

最后的图解评估了群集1的20个最显著富集的途径。路径节点的大小对应于所涉及的基因的数量,并且边缘的宽度对应于路径之间重叠的数量基因。可以看出,翻译中涉及的所有途径都是高度重叠的。mRNA相关通路在图中形成另一高度连接的组分。EGFR1通路与许多其它途径强重叠,表明受这些途径影响的基因参与了类似的分子机制。

Sarcoma
肉瘤

After lung and ovarian cancers, next we will focus on sarcoma. Sarcomas are a heterogeneous group of malignant tumors that are relatively rare. They are typically categorized according to the morphology and type of connective tissues that they arise in, including fat, muscle, blood vessels, deep skin tissues, nerves, bones and cartilage, which comprises less than 10% of all malignancies (Jain 2010). Sarcomas can occur anywhere in the human body, from head to foot, can develop in patients of any age including children, and often vary in aggressiveness, even within the same organ or tissue subtype (Honore 2015). This suggests that a histological description by organ and tissue type is neither sufficient for categorization of the disease nor does it help in selecting the most optimal treatment.

在肺癌和卵巢癌之后,接下来我们将关注肉瘤。肉瘤是一组罕见的恶性肿瘤。它们通常根据它们所产生的结缔组织的形态和类型来分类,包括脂肪、肌肉、血管、深部皮肤组织、神经、骨骼和软骨,其中包括不到10%的所有恶性肿瘤(JAIN 2010)。肉瘤可以发生在人体的任何地方,从头到脚,可以在任何年龄的儿童中发展,并且经常在攻击性上变化,即使在相同的器官或组织亚型(HONER 2015)中。这表明器官和组织类型的组织学描述既不足以分类疾病,也不利于选择最理想的治疗方法。

Diagnosing sarcomas poses a particular dilemma, not only due to their rarity, but also due to their diversity, with more than 70 histological subtypes, and our insufficient understanding of the molecular characteristics of these subtypes (Jain 2010).

诊断肉瘤提出了一个特殊的困境,不仅由于其稀有,但也由于其多样性,超过70个组织亚型,我们对这些亚型的分子特征的理解不足(JAIN 2010)。

Therefore, recent research studies focused on molecular classifications of sarcomas based on genetic alterations, such as fusion genes or oncogenic mutations. While research achieved major developments in local control/limb salvage, the survival rate for “high-risk” soft tissue sarcomas (STSs) has not improved significantly, especially in patients with a large, deep, high-grade sarcoma (stage III) (Kane III 2018).

因此,最近的研究集中在肉瘤的分子分类的基础上,如融合基因或致癌突变的遗传改变。虽然研究取得了重大进展,局部控制/保肢,“高风险”软组织肉瘤(STSS)的生存率并没有得到显著改善,尤其是在大,深,高级别肉瘤患者(III期)(Kane III 2018)。

For these reasons, in the next phase of World Community Grid analysis, we will focus on the evaluation of the genomic background of sarcoma. We will utilize different sequencing information and technologies to gain a broader knowledge between the different levels of genetic aberrations and the regulational implications. We will provide a more detailed description of the data and the incentives in the next update.

由于这些原因,在下一阶段的世界社区网格分析中,我们将着重于对肉瘤基因组背景的评估。我们将利用不同的测序信息和技术,以获得更广泛的知识之间的不同水平的遗传变异和调节的含义。我们将在下一次更新中提供数据和激励的更详细的描述。

  • Petschnigg J, Kotlyar M, Blair L, Jurisica I, Stagljar I, and Ketteler R, Systematic identification of oncogenic EGFR interaction partners, J Mol Biol, 429(2): 280-294, 2017.
  • Petschnigg, J., Groisman, B., Kotlyar, M., Taipale, M., Zheng, Y., Kurat, C., Sayad, A., Sierra, J., Mattiazzi Usaj, M., Snider, J., Nachman, A., Krykbaeva, I., Tsao, M.S., Moffat, J., Pawson, T., Lindquist, S., Jurisica, I., Stagljar, I. Mammalian Membrane Two-Hybrid assay (MaMTH): a novel split-ubiquitin two-hybrid tool for functional investigation of signaling pathways in human cells; Nat Methods, 11(5):585-92, 2014.
  • Rahmati, S., Abovsky, M., Pastrello, C., Jurisica, I. pathDIP: An annotated resource for known and predicted human gene-pathway associations and pathway enrichment analysis. Nucl Acids Res, 45(D1): D419-D426, 2017.
  • Kane, John M., et al. "Correlation of High-Risk Soft Tissue Sarcoma Biomarker Expression Patterns with Outcome following Neoadjuvant Chemoradiation." Sarcoma 2018 (2018).
  • Jain, Shilpa, et al. "Molecular classification of soft tissue sarcomas and its clinical applications." International journal of clinical and experimental pathology 3.4 (2010): 416.
  • Honore, C., et al. "Soft tissue sarcoma in France in 2015: epidemiology, classification and organization of clinical care." Journal of visceral surgery 152.4 (2015): 223-230.
  • Tokar T, Pastrello C, Ramnarine VR, Zhu CQ, Craddock KJ, Pikor L, Vucic EA, Vary S, Shepherd FA, Tsao MS, Lam WL, Jurisica Differentially expressed microRNAs in lung adenocarcinoma invert effects of copy number aberrations of prognostic genes. Oncotarget. 9(10):9137-9155, 2018
  • Becker-Santos, D.D., Thu, K.L, English, J.C., Pikor, L.A., Chari, R., Lonergan, K.M., Martinez, V.D., Zhang, M., Vucic, E.A., Luk, M.T.Y., Carraro, A., Korbelik, J., Piga, D., Lhomme, N.M., Tsay, M.J., Yee, J., MacAulay, C.E., Lockwood, W.W., Robinson, W.P., Jurisica, I., Lam, W.L., Developmental transcription factor NFIB is a putative target of oncofetal miRNAs and is associated with tumour aggressiveness in lung adenocarcinoma, J Pathology, 240(2):161-72, 2016.
  • Cinegaglia, N.C., Andrade, S.C.S., Tokar, T., Pinheiro, M., Severino, F. E., Oliveira, R. A., Hasimoto, E. N., Cataneo, D. C., Cataneo, A.J.M., Defaveri, J., Souza, C.P., Marques, M.M.C, Carvalho, R. F., Coutinho, L.L., Gross, J.L., Rogatto, S.R., Lam, W.L., Jurisica, I., Reis, P.P. Integrative transcriptome analysis identifies deregulated microRNA-transcription factor networks in lung, adenocarcinoma, Oncotarget, 7(20): 28920-34, 2016.


Other news
其他新闻

We have secured a major funding from Ontario Government for our research: The Next Generation Signalling Biology Platform. The main goal of the project is developing novel integrated analytical platform and workflow for precision medicine. This project will create an internationally accessible resource that unifies different types of biological data, including personal health information—unlocking its full potential and making it more usable for research across the health continuum: from genes and proteins to pathways, drugs and humans.

我们已经获得了安大略政府为我们的研究提供的主要资金:下一代信号生物学平台。该项目的主要目标是开发新的精密医疗分析平台和工作流程。该项目将创建一个国际可访问的资源,统一不同类型的生物数据,包括个人健康信息解锁其全部潜力,并使其更适用于跨健康连续性的研究:从基因和蛋白质到通路、药物和HU。曼斯。

We have also published papers describing several tools, portals and applications with our collaborators. Below we list those most related directly or indirectly to work on World Community Grid:

我们也发表了一些描述我们合作者的工具、门户和应用的论文。下面我们直接或间接地列出那些与世界社区网格相关的工作:

  • Wong, S., Pastrello, C., Kotlyar, M., Faloutsos, C., Jurisica, I. SDREGION: Fast spotting of changing communities in biological networks. ACM KDD Proceedings, 2018. In press. BMC Cancer, 18(1):408, 2018.
  • Kotlyar, M., Pastrello, C., Rossos, A., Jurisica, I. Protein-protein interaction databases. Eds. Cannataro, M. et al. Encyclopedia of Bioinformatics and Computational Biology, 81, Elsevier. In press. doi.org/10.1016/B978-0-12-811414-8.20495-1
  • Rahmati, S., Pastrello, C., Rossos, A., Jurisica, I. Two Decades of Biological Pathway Databases: Results and Challenges, Eds. Cannataro, M. et al. Encyclopedia of Bioinformatics and Computational Biology, 81, Elsevier. In press.
  • Hauschild, AC, Pastrello, C., Rossos, A., Jurisica, I. Visualization of Biomedical Networks, Eds. Cannataro, M. et al. Encyclopedia of Bioinformatics and Computational Biology, 81, Elsevier. In press.
  • Sivade Dumousseau M, Alonso-López D, Ammari M, Bradley G, Campbell NH, Ceol A, Cesareni G, Combe C, De Las Rivas J, Del-Toro N, Heimbach J, Hermjakob H, Jurisica I, Koch M, Licata L, Lovering RC, Lynn DJ, Meldal BHM, Micklem G, Panni S, Porras P, Ricard-Blum S, Roechert B, Salwinski L, Shrivastava A, Sullivan J, Thierry-Mieg N, Yehudi Y, Van Roey K, Orchard S. Encompassing new use cases - level 3.0 of the HUPO-PSI format for molecular interactions. BMC Bioinformatics, 19(1):134, 2018.
  • Minatel BC, Martinez VD, Ng KW, Sage AP, Tokar T, Marshall EA, Anderson C, Enfield KSS, Stewart GL, Reis PP, Jurisica I, Lam WL., Large-scale discovery of previously undetected microRNAs specific to human liver. Hum Genomics, 12(1):16, 2018.
  • Tokar T, Pastrello C, Ramnarine VR, Zhu CQ, Craddock KJ, Pikor L, Vucic EA, Vary S, Shepherd FA, Tsao MS, Lam WL, Jurisica, I. Differentially expressed microRNAs in lung adenocarcinoma invert effects of copy number aberrations of prognostic genes. Oncotarget. 9(10):9137-9155, 2018.
  • Paulitti A, Corallo D, Andreuzzi E, Bizzotto D, Marastoni S, Pellicani R, Tarticchio G, Pastrello C, Jurisica I, Ligresti G, Bucciotti F, Doliana R, Colladel R, Braghetta P, Di Silvestre A, Bressan G, Colombatti A, Bonaldo P, Mongiat M. Matricellular EMILIN2 protein ablation ca 1 uses defective vascularization due to impaired EGFR-dependent IL-8 production, Oncogene, Feb 27. doi: 10.1038/s41388-017-0107-x. [Epub ahead of print] 2018.
  • Tokar, T., Pastrello, C., Rossos, A., Abovsky, M., Hauschild, A.C., Tsay, M., Lu, R., Jurisica. I. mirDIP 4.1 – Integrative database of human microRNA target predictions, Nucl Acids Res, D1(46): D360-D370, 2018.
  • Kotlyar M., Pastrello, C., Rossos, A., Jurisica, I., Prediction of protein-protein interactions, Current Protocols in Bioinf, 60, 8.2.1–8.2.14., 2017.
  • Singh, M., Venugopal, C., Tokar, T., Brown, K.B., McFarlane, N., Bakhshinyan, D., Vijayakumar, T., Manoranjan, B., Mahendram, S., Vora, P., Qazi, M., Dhillon, M., Tong, A., Durrer, K., Murty, N., Hallet, R., Hassell, J.A., Kaplan, D., Jurisica, I., Cutz, J-C., Moffat, J., Singh, D.K., RNAi screen identifies essential regulators of human brain metastasis initiating cells, Acta Neuropathologica, 134(6):923-940, 2017.


Thank you
致谢

This work would not be possible without the participation of World Community Grid Members. Thank you for generously contributing CPU cycles, and for your interest in this and other World Community Grid projects.

没有世界社区网格成员的参与,这项工作是不可能进行的。感谢您慷慨贡献CPU周期,以及您对这个和其他世界社区网格项目的兴趣。


=========
那啥,上面是机翻哈,可能有诸多不正确的地方,等大神来指点。

----------
大意
----------
当前阶段是收集卵巢癌的数据,并继续分析肺癌的数据。
下一种癌症——肉瘤——即将加入该项目,作为下一个阶段的重点。

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参与人数 1维基拼图 +100 收起 理由
zhouxiaobo + 100 大神 膜拜一下(

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发表于 2018-8-31 09:45:14 | 显示全部楼层
本帖最后由 0xCAFEBABE 于 2018-8-31 09:48 编辑

BOINC Developers and Leaders Gather in the UK

30 八月 2018

摘要
This year's annual BOINC Workshop was held at University of Oxford and focused on the BOINC platform's future development.



This graphic was part of Kevin Reed's presentation about the BOINC community and how it works.

The Oxford e-Research Centre at University of Oxford recently hosted theBOINC Workshop 2018.

BOINC, which stands for Berkeley Open Infrastructure for Network Computing, is an open-source software platform that supports volunteer computing. You can learn more about how BOINC is structured here.

World Community Grid project manager Juan Hindo, and technical team members Kevin Reed and Keith Uplinger, represented World Community Grid at the event.

This year's workshop included topics such as:

  • How the new GDPR regulations may affect BOINC projects
  • BOINC's technical development over the past year
  • Discussion of BOINC review, testing, and release processes
  • Overview of current BOINC projects
  • An open discussion on working together for the betterment of BOINC


Kevin Reed, who serves as Chairman of the BOINC Project Management Committee (PMC), gave a presentation on the development of the BOINC community. Keith Uplinger, Secretary of the BOINC PMC, discussed Google Test (a unit testing library for C++). Juan Hindo gave the group an overview of World Community Grid to the group.

You can see all of the presentations from the workshop here, and listen to audio from the conference here.


=====大意=====
牛津大学电子研究中心最近主办了 2018 BONC 研讨会,WCG 的项目经理 Juan Hindo 和技术人员 Kevin Reed、Keith Uplinger 出席了会议。
会议主要讨论的内容如下:
  • 新的 GDPR 规则如何影响 BOINC 项目
  • BOINC 过去一年的技术发展
  • BOINC 审查、测试和发布过程的讨论
  • BOINC 项目综述
  • 关于共同改善 BOINC 的公开讨论

通过这两个网址可以看到会议上所有的演讲和音频。
https://drive.google.com/drive/f ... AY2OiiEdykfFLYG5Tc4
https://drive.google.com/drive/f ... lbCHEAVFjvqjVdYWMCU

=====层主吐槽=====
话说我们不是也有个偷偷改造 BOINC 的小计划嘛,好想去看看大佬们的技术讨论和平台未来的发展是怎么打算的呀。
可是我觉得我听不懂。。要是有论坛里的大佬来给指导下就好了。。。逃:)

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发表于 2018-9-18 23:17:48 | 显示全部楼层

2018-09-17: World Community Grid, THOR Challenge Aims for New Heights in 2018

CRUNCHERS SANS FRONTIERES, one of World Community Grid's most dedicated teams, issues the THOR Challenge each fall. Find out how you and your team can join this year's challenge and beat last year's results.







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看起来是团队赛,有兴趣吗?
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