ISCB COVID-19 Section

The COVID-19 pandemic is both severely affecting our lives and impacting our science. ISCB responds to the respective challenges by offering its expertise to the scientific community and empowering scientific networking. The ISCB COVID-19 Section offers four lines of this initiative:

• ISCB COVID-19 Statements. Here you find statements on the ongoing pandemic that have been issued by ISCB.
• ISCB COVID-19 Webinar collection. Here you find webinars specific to the topics of COVID-19 and Sars Cov-2 that are organized by ISCB.
• ISCB COVID-19 Science collection. Here you find materials specific to the topics of COVID-19 and Sars Cov-2 that have been submitted by ISCB members. This collection has three subsections for (i) scientific articles, (ii) scientific data sets and, (iii) proposals of community science projects.
• ISCB Tutorial collection. Here you find tutorials that present basic or advanced computational biology content for biologists and computational biologists in these times of increased digital education activity. The tutorials have been (i) presented at recent ISCB conferences and (ii) suggested by ISCB members.

Call for submissions

If you are a member of ISCB we encourage you to submit entries to the Science collection and Tutorial collection. Your submission entails a pointer to the science content, a short description of background or purpose (two lines) and lists your name as submitter. Submission will be subjected to a basic check of scope and purpose.

You find the relevant submission forms here.

ISCB COVID-19 Webinar Collection

The ISCB COVID-19 webinar collection points to webinars on ongoing research on COVID-19 and Sars-Cov2.  The webianrs are split into two lists

1. A list of recent ISCBacademy COVID-19 webinars
2. A list of presentations given at ISMB 2020

ISCBacademy Covid-19 Webinars

A SARS-CoV-2 protein interaction map reveals targets for drug repurposing
By Nevan Krogan

May 19, 2020

Efforts to develop antiviral drugs versus COVID-19 or vaccines for its prevention have been hampered by limited knowledge of the molecular details of SARS-CoV-2 infection. This webinar will describe our efforts to address this challenge by expressing 26 of the 29 SARS-CoV-2 proteins in human cells and identifying the human proteins physically associated with each using affinity-purification mass spectrometry. Among 332 high-confidence SARS-CoV-2-human protein-protein interactions, we identified 66 druggable human proteins or host factors targeted by 69 compounds (29 FDA-approved drugs, 12 drugs in clinical trials, and 28 preclinical compounds). Within a subset of these, multiple viral assays identified two sets of pharmacological agents that displayed antiviral activity.

Click here to watch

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At Home with Covid-19
By Brian Shoichet

June 26, 2020

The urgency of the coronavirus pandemic has motivated investigators world wide to seek approved drugs or investigation new drugs as a way to rapidly advance therapeutics into clinical trials to treat the disease.  I will describe a large collaboration, hosted by the UCSF Quantitative Biology Institute, to do that in a mechanistically focused way.  Using AP-MS, a host-pathogen network of viral and human proteins was created, and drugs were sought targeting the human partner.  From among 322 high confidence human proteins associated with 26 viral proteins emerged 63 that were druggable.  Against those, 69 drugs were tested for efficacy, and from these 10 drugs in two broad classes emerged: those targeting protein biogenesis, and those acting against the Sigma1 and Sigma2 receptors.  The activities of these drugs, and the chemoinformatics infrastructure that supported their selection, will be discussed.  The mechanism-based repurposing strategy will be compared to a complementary effort that targets viral proteins and seeks novel chemical matter, using structure-based ultra-large library docking.

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Global surveillance of COVID-19 by mining news media using a multi-source dynamic embedded topic model
By Yue Li and David Buckeridge

June 30, 2020

As the COVID-19 pandemic continues to unfold, understanding the global impact of non-pharmacological interventions (NPI) is important for formulating effective intervention strategies, particularly as many countries prepare for future waves. We used a machine learning approach to distill latent topics related to NPI from large-scale international news media. We hypothesize that these topics are informative about the timing and nature of implemented NPI, dependent on the source of the information (e.g., local news versus official government announcements) and the target countries. Given a set of latent topics associated with NPI (e.g., self-quarantine, social distancing, online education, etc), we assume that countries and media sources have different prior distributions over these topics, which are sampled to generate the news articles. To model the source-specific topic priors, we developed a semi-supervised, multi-source, dynamic, embedded topic model. Our model is able to simultaneously infer latent topics and learn a linear classifier to predict NPI labels using the topic mixtures as input for each news article. To learn these models, we developed an efficient end-to-end amortized variational inference algorithm. We applied our models to news data collected and labelled by the World Health Organization (WHO) and the Global Public Health Intelligence Network (GPHIN). Through comprehensive experiments, we observed superior topic quality and intervention prediction accuracy, compared to the baseline embedded topic models, which ignore information on media source and intervention labels. The inferred latent topics reveal distinct policies and media framing in different countries and media sources, and also characterize reaction COVID-19 and NPI in a semantically meaningful manner.

Click here to watch

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Evolutionary origins of SARS-CoV-2 and tracking its spread using phylodynamic data integration
By Philippe Lemey

October 2, 2020 at 11:00AM EDT!

There are outstanding evolutionary questions on the recent emergence of human coronavirus SARS-CoV-2 including the role of reservoir species, the role of recombination, and its time of divergence from animal viruses. I will describe a collaborative effort to reconstruct the origins of the virus. Our findings indicate that sarbecoviruses – the viral subgenus containing SARS-CoV and SARS-CoV-2 – undergo frequent recombination and exhibit spatially structured genetic diversity on a regional scale in China. Contrary to other analyses, we find that SARS-CoV-2 itself is not a recombinant of any sarbecoviruses detected to date, and its receptor binding motif, important for specificity to human ACE2 receptors, appears to be an ancestral trait shared with bat viruses, not one acquired recently via recombination. Divergence dates between SARS-CoV-2 and the bat sarbecovirus reservoir indicates that the lineage giving rise to SARS-CoV-2 has been circulating unnoticed in bats for decades.

Following the emergence of the virus, unprecedented sequencing efforts have resulted in the accumulation of over 100,000 genome sequences sampled globally. Despite this rich source of information, evolutionary reconstructions are hindered by the slow accumulation of sequence divergence over its relatively short transmission history and the spatiotemporal bias in genome sequence sampling. I will describe a data phylodynamic data integration approach in a Bayesian framework to tries to address these issues in order to assist molecular epidemiological analyses.

Click here to register

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ISMB 2020 COVID-19 Related Presentations

Links within this section: COVID-19 Session | Other ISMB tracks

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ISCB COVID-19 Tutorial Collection

Below is a list of tutorials on general computational biology issues for use by computational biologists and bench scienists in this time of added digital education activities. The are two lists;

1. A list of tutorials presented at recent ISMB meetings
2. A list of tutorials submitted by ISCB members.

Tutorials and Special Sessions Presented at Recent ISMB Meetings

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Tutorials Submitted by ISCB Members

To submit a tutorial to be added to the collection use the submission form.

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ISCB COVID-19 Collection Submission Forms

ISCB COVID-19 Science Collection

• To submit a scientific article to the ISCB COVID-19 science collection use this form.
• To submit a scientific data set to the ISCB COVID-19 science collection use this form.
• To propose a community science project to the ISCB COVID-19 science collection use this form or submit a proposal to This email address is being protected from spambots. You need JavaScript enabled to view it.
  

ISCB COVID-19 Tutorial Collection

• To submit a tutorial to the ISCB COVID-19 tutorial collection use this form.