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Sanjana Gupta received the DCSB Best Student of the Year Award for 2019 at the CSB Annual Appreciation lunch

Sanjana here with her co-advisors, Dr. James R. Faeder (l) and Dr. Robin E.C. Lee (r).

Sanjana Gupta received the DCSB Best PhD Student of the Year Award for 2019 at the CSB Annual Appreciation lunch held at the University Club on Pitt’s Oakland campus, December 4, 2019. She was nominated by her co-advisors, Dr. James R. Faeder and Dr. Robin E.C. Lee for her current work on addressing the question of parameterization of mechanistic models of signal transduction. Sanjana has developed an approach based on Lasso regularization commonly used in genomics to fitting mechanistic models in order to obtain reduced or parsimonious models that describe cellular responses under specific conditions. An abstract describing this work was accepted for a talk at the recent Q-bio Conference and her presentation there was very well-received. Several members of the science community contacted both Jim and Robin to express their enthusiasm with Sanjana’s presentation and current research. A pre-print of this work is available on bioRxiv, Parallel Tempering with Lasso for Model Reduction in Systems Biology. A manuscript of that preprint is under revision with PloS Computational Biology. Overall, Sanjana has made outstanding progress in her research during the previous year and is poised to publish several papers in the beginning of 2020 that will have a strong impact on the entire systems biology community. Congratulations Sanjana!

Koes Lab Members Win NCATS ASPIRE Challenge

(left to right) Paul Francoeur, Jonathan King, David Koes, Jocelyn Sunseri, Matthew Ragoza

Dr. Koes and his lab members were among the winners of the NCATS ASPIRE 2018 Award for the following project:

Deep and Generative Structure-Based Models for Drug Discovery

Dr. David Koes
Dr. Matthew Ragoza
Jocelyn Sunseri
Paul Francoeur
Jonathan King

The project team proposes to make open source tools and resources available to researchers that enable the rapid identification and optimization of small molecule therapeutics for structure-enabled molecular targets for pain and opioid abuse.

The goal of the 2018 NCATS ASPIRE Design Challenges is to generate innovative and catalytic approaches toward solving the opioid crisis through the development of next-generation addiction-free analgesics with new chemistries, data-mining and analytical tools and technologies, as well as biological assays that will revolutionize discovery, development and pre-clinical testing of new and safer treatments for pain, opioid use disorder (OUD) and overdose.

The Lee lab develop a dynamic stimulation system to probe signal transduction networks in single cells

Using open-source parts and 3D-printed components, the Lee lab develops a robotic system for mammalian cell cultures that accurately reproduces user-defined concentration profiles for one or more stimuli, such as cytokines or drugs. The team applies the dynamic stimulation system to investigate NF-kB signaling in single cells exposed to time-varying concentrations of TNF, a molecular network that is often deregulated in autoimmunity and cancer. Cellular responses to dynamic stimuli reveals context-dependent sensitivities and new classes of single cell responses that are distinct from the canonical NF-kB response during persistent stimulation. Guided by computational modeling, the team show that new response classes can be modulated with chemicals that target rates for basal cellular processes, including transcription and translation.

Taken together, the work shows that dynamic stimuli can be used to more accurately recapitulate biological complexity, to reveal hidden capabilities of biological systems, and to provide new opportunities to rationally manipulate disease-associated signaling mechanisms.

Mokashi CS, Schipper DL, Qasaimeh MA, Lee REC. A System for Analog Control of Cell Culture Dynamics to Reveal Capabilities of Signaling Networks. (2019) iScience [Epub ahead of print]

Weiguang Mao and Dr. Maria Chikina Publish in Nature Methods

Pathway-level information extractor (PLIER): a new tool to quantify pathway level effects in gene expression data

A major challenge in gene expression analysis is to accurately infer relevant biological insights, such as variation in cell-type proportion or pathway activity, from global gene expression studies. We present pathway-level information extractor (PLIER), a broadly applicable solution for this problem that outperforms available cell proportion inference algorithms and can automatically identify specific pathways that regulate gene expression. Our method improves interstudy replicability and reveals biological insights when applied to trans-eQTL (expression quantitative trait loci) identification.

Mao W, Zaslavsky E, Hartmann BM, Sealfon SC, Chikina M. Pathway-level information extractor (PLIER) for gene expression data. Nature Methods; 16, 607–610 (2019)

 

Weiguang Mao Maria Chikina, PhD

Dr. Joseph Ayoob Named NRMN Mentor of the Month

Dr. Joeseph Ayoob was named as the National Research Mentoring Network Mentor of the Month for July 2019, where he is also one of only four NRMN’s Master Mentors.  Dr. Ayoob is an Associate Professor in the Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh.  Additionally, he is the Founding Program Director of our NSF-funded Training and Experimentation in Computational Biology (TECBio) Research Experience for Undergraduates (REU) Program and the UPMC Hillman Cancer Center and University of Pittsburgh’s Computational Biology Research Academy (CoBRA) for outstanding high-school scholars.  Dr. Ayoob is also the Co-Founding Program Director for our CPCB MetaSchool Graduate Student Professional Development Series and the Course Director for Laboratory Methods for Computational Biologists, part of our Joint Carnegie Mellon/Pitt, Ph.D. Program in Computational Biology (CPCB), as well as the Co-Founding Director for the Computational Biomedicine & Biotechnology Masters Program (COBB). Click here to read more about his story as a scientist and mentor.

About the program:

Despite several decades of efforts to increase diversity in the U.S. biomedical workforce, the issue of the under-representation of many populations remains.  Scholars from non-majority backgrounds–whether by race, ethnicity, socioeconomic status, sexual orientation, or disability–have overcome many barriers yet still carry the burdens of disadvantaged and discrimination.  NRMN is funded by NIH and is a part of the NIH Diversity Program Consortium (DPC), which is a national collaborative that develops, implements, and determines the effectiveness of innovative approaches to strengthen institutional capacity to sustain mentor-mentee relationships. The NRMN is a nationwide consortium of biomedical professionals and institutions collaborating to provide enhanced networking and mentorship experiences in support of the training and career development of individuals from under represented backgrounds who are pursuing biomedical, behavioral, clinical, and social science research careers (collectively termed biomedical research careers). The NRMN is intended to enable mentees across career stages to find effective mentors who will engage in productive, supportive, and culturally responsive mentoring relationships.  The NRMN monthly newsletter serves over 15,000 researchers around the country across all career stages in the biomedical sciences.