R01DA051906 (PI Gerstein)
07/15/20 - 05/31/25
NIDA
A Big Data Approach to Identify Epigenetic, Transcriptomic, and Network Dynamics as Immune Dysfunction Drivers Associated with HIV Infection and Substance Use Disorder
Role: Contact PI/Project Leader

The proposed study is to leverage high-dimensional, multi-scale, and highly heterogeneous genomics data to discover the essential molecular alterations of immune cells introduced by HIV and/or substance use disorder (SUD) at a single-cell resolution. We propose a computational framework to depict the comprehensive immune cell regulome, construct molecular networks of various cell types, and pinpoint key immune dysfunction driver events at a single-cell resolution.

Related material:

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Improved Prediction of Ligand-Protein Binding Affinities by Meta-modeling
HJ Lee, PS Emani, MB Gerstein (2024). J Chem Inf Model 64: 8684-8704.

MolLM: A Unified Language Model to Integrate Biomedical Text with 2D and 3D Molecular Representations
X Tang, A Tran, J Tan, MB Gerstein (2024). Bioinformatics 40: i357-i368.

Latent Evolutionary Signatures: A General Framework for Analyzing Music and Cultural Evolution
J Warrell, L Salichos, M Gancz, MB Gerstein (2024). J R Soc Interface 21: 20230647.

Less-is-more: selecting transcription factor binding regions informative for motif inference
J Xu, J Gao, P Ni, M Gerstein (2024). Nucleic Acids Res 52: e20.

Genetic determination of regional connectivity in modelling the spread of COVID-19 outbreak for more efficient mitigation strategies
L Salichos, J Warrell, H Cevasco, A Chung, M Gerstein (2023). Sci Rep 13: 8470.

Constructing a multiple-layer interactome for SARS-CoV-2 in the context of lung disease: Linking the virus with human genes and co-infecting microbes
S Lou, M Yang, T Li, W Zhao, H Cevasco, YT Yang, M Gerstein (2023). PLoS Comput Biol 19: e1011222.

Venus: An efficient virus infection detection and fusion site discovery method using single-cell and bulk RNA-seq data.
CY Lee, Y Chen, Z Duan, M Xu, MJ Girgenti, K Xu, M Gerstein, J Zhang (2022). PLoS Comput Biol 18: e1010636.

DECODE: a Deep-learning framework for Condensing enhancers and refining boundaries with large-scale functional assays.
Z Chen, J Zhang, J Liu, Y Dai, D Lee, MR Min, M Xu, M Gerstein (2021). Bioinformatics 37: i280-i288.

Establishing a Global Standard for Wearable Devices in Sport and Exercise Medicine: Perspectives from Academic and Industry Stakeholders.
GI Ash, M Stults-Kolehmainen, MA Busa, AE Gaffey, K Angeloudis, B Muniz-Pardos, R Gregory, RA Huggins, NS Redeker, SA Weinzimer, LA Grieco, K Lyden, E Megally, I Vogiatzis, L Scher, X Zhu, JS Baker, C Brandt, MS Businelle, LM Fucito, S Griggs, R Jarrin, BJ Mortazavi, T Prioleau, W Roberts, EK Spanakis, LM Nally, A Debruyne, N Bachl, F Pigozzi, F Halabchi, DA Ramagole, DC Janse van Rensburg, B Wolfarth, C Fossati, S Rozenstoka, K Tanisawa, M Borjesson, JA Casajus, A Gonzalez-Aguero, I Zelenkova, J Swart, G Gursoy, W Meyerson, J Liu, D Greenbaum, YP Pitsiladis, MB Gerstein (2021). Sports Med 51: 2237-2250.

Bayesian structural time series for biomedical sensor data: A flexible modeling framework for evaluating interventions.
J Liu, DJ Spakowicz, GI Ash, R Hoyd, R Ahluwalia, A Zhang, S Lou, D Lee, J Zhang, C Presley, A Greene, M Stults-Kolehmainen, LM Nally, JS Baker, LM Fucito, SA Weinzimer, AV Papachristos, M Gerstein (2021). PLoS Comput Biol 17: e1009303.

Gene Tracer: a smart, interactive, voice-controlled Alexa skill For gene information retrieval and browsing, mutation annotation and network visualization.
S Lou, T Li, J Liu, M Gerstein (2021). Bioinformatics 37: 2998-3000.

Weight-based Neural Network Interpretability using Activation Tuning and Personalized Products
H Mohsen, J Warrell, MR Min, S Negahban, M Gerstein (2020). The 15th Machine Learning in Computational Biology Workshop.

Latent-space embedding of expression data identifies gene signatures from sputum samples of asthmatic patients.
S Lou, T Li, D Spakowicz, X Yan, GL Chupp, M Gerstein (2020). BMC Bioinformatics 21: 457.

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