108 citations
- University of Wisconsin–MadisonUS38 papers
- Santa Fe InstituteUS4 papers
- Harvard UniversityUS3 papers
- University of MichiganUS3 papers
- Brigham and Women's HospitalUS2 papers
- California Institute of TechnologyUS2 papers
- Carnegie Mellon UniversityUS2 papers
- Georgia Institute of TechnologyUS2 papers
- Massachusetts General HospitalUS2 papers
- Massachusetts Institute of TechnologyUS2 papers
- Morgridge Institute for ResearchUS2 papers
- Princeton UniversityUS2 papers
46 papers
MERLIN-SUITE: Probabilistic modular GRN inference from multi-omics data integrating regulatory priors and transcription factor activity
Suvojit Hazra, Marina Kotvanova, Kirstan Gimse +1
Accurately reconstructing gene regulatory networks (GRNs) is essential for understanding transcriptional processes in development and disease. MERLIN-SUITE (https://github.com/Roy-…
scMTNI: Leveraging cellular trajectory and context to infer dynamic GRNs from single-cell multi-omics data
Suvojit Hazra, Chandrani Kumari, Sushmita Roy
Transcriptional gene regulatory networks (GRNs) depict the directed relationships between regulators and target genes, determining gene expression patterns in a cell-type-specific…
Modeling Dynamics, Cell Type Specificity, and Perturbations in Gene Regulatory Networks
Junha Shin, Spencer Halberg-Spencer, Yuda Liu +3
Gene regulatory networks (GRNs) define the regulatory relationships among molecules such as transcription factors, chromatin remodelers, and target genes. GRNs play a critical role…
Semi-Supervised Contrastive Learning with Orthonormal Prototypes
Huanran Li, Manh Nguyen, Daniel Pimentel-Alarcón
Contrastive learning has emerged as a powerful method in deep learning, excelling at learning effective representations through contrasting samples from different distributions. Ho…
Nonnegative Matrix Factorization through Cone Collapse
Manh Nguyen, Daniel Pimentel-Alarcón
Nonnegative matrix factorization (NMF) is a widely used tool for learning parts-based, low-dimensional representations of nonnegative data, with applications in vision, text, and b…
Current and future directions in network biology
Marinka Zitnik, Michelle M. Li, Aydin Wells +34
Network biology is an interdisciplinary field bridging computational and biological sciences that has proved pivotal in advancing the understanding of cellular functions and diseas…