A5033642313- Bioinformatics and Genomic Networks
- Scientific Computing and Data Management
- Single-cell and spatial transcriptomics
- Genomics and Phylogenetic Studies
- Gene expression and cancer classification
- Genetic Associations and Epidemiology
- RNA Research and Splicing
- Cell Image Analysis Techniques
- SARS-CoV-2 and COVID-19 Research
- RNA modifications and cancer
- COVID-19 Clinical Research Studies
- Hepatitis C virus research
- Genomics and Chromatin Dynamics
- Amyotrophic Lateral Sclerosis Research
- Liver Disease Diagnosis and Treatment
- Cancer Mechanisms and Therapy
- Gene Regulatory Network Analysis
- Research Data Management Practices
- Mitochondrial Function and Pathology
- Cancer Genomics and Diagnostics
- Epigenetics and DNA Methylation
- 14-3-3 protein interactions
- Endoplasmic Reticulum Stress and Disease
- Immune cells in cancer
- DNA Repair Mechanisms
Icahn School of Medicine at Mount Sinai
2017-2025
Kettering University
2025
Illumina (United States)
2017-2020
Library Network
2020
University of Miami
2017-2018
Mount Sinai Medical Center
2018
Miami University
2017
University of Cincinnati
2017
Azienda Ospedaliera Universitaria Policlinico "G. Martino"
2011
Identifying the transcription factors (TFs) responsible for observed changes in gene expression is an important step understanding regulatory networks. ChIP-X Enrichment Analysis 3 (ChEA3) a factor enrichment analysis tool that ranks TFs associated with user-submitted sets. The ChEA3 background database contains collection of set libraries generated from multiple sources including TF-gene co-expression RNA-seq studies, TF-target associations ChIP-seq experiments, and co-occurrence computed...
RNA sequencing (RNA-seq) is the leading technology for genome-wide transcript quantification. However, publicly available RNA-seq data currently provided mostly in raw form, a significant barrier global and integrative retrospective analyses. ARCHS4 web resource that makes majority of published from human mouse at gene levels. For developing ARCHS4, FASTQ files experiments Gene Expression Omnibus (GEO) were aligned using cloud-based infrastructure. In total 187,946 samples are accessible...
While gene expression data at the mRNA level can be globally and accurately measured, profiling activity of cell signaling pathways is currently much more difficult.eXpression2Kinases (X2K) computationally predicts involvement upstream pathways, given a signature differentially expressed genes.X2K first computes enrichment for transcription factors likely to regulate genes.The next step X2K connects these enriched through known protein-protein interactions (PPIs) construct subnetwork.The...
The Library of Integrated Network-based Cellular Signatures (LINCS) program is a national consortium funded by the NIH to generate diverse and extensive reference library cell-based perturbation-response signatures, along with novel data analytics tools improve our understanding human diseases at systems level. In contrast other large-scale generation efforts, LINCS Data Signature Generation Centers (DSGCs) employ wide range assay technologies cataloging cellular responses. Integration of,...
Phosphoproteomics and proteomics experiments capture a global snapshot of the cellular signaling network, but these methods do not directly measure kinase state. Kinase Enrichment Analysis 3 (KEA3) is webserver application that infers overrepresentation upstream kinases whose putative substrates are in user-inputted list proteins. KEA3 can be applied to analyze data from phosphoproteomics studies predict responsible for observed differential phosphorylations. The background database contains...
The frequency by which genes are studied correlates with the prior knowledge accumulated about them. This leads to an imbalance in research attention where some highly investigated while others ignored. Geneshot is a search engine developed illuminate this gap and promote under-studied genome. Through simple web interface, enables researchers enter arbitrary terms, receive ranked lists of relevant terms. Returned gene contain that were previously published association as well predicted be...
Abstract The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic states associated with diverse diseases. To develop detailed understanding the linkage between changes, we generated comprehensive dataset that catalogs transcriptional, proteomic, epigenomic responses MCF10A mammary epithelial cells...
Abstract Human preimplantation development involves extensive remodeling of RNA expression and splicing. However, its transcriptome has been compiled using short-read sequencing data, which fails to capture most full-length mRNAs. Here, we generate an isoform-resolved early human by performing long- on 73 embryos spanning the zygote blastocyst stages. We identify 110,212 unannotated isoforms transcribed from known genes, including highly conserved protein-coding loci key developmental...
Abstract PRDM (PRDI-BF1 and RIZ homology domain containing) family members are sequence-specific transcriptional regulators involved in cell identity fate determination, often dysregulated cancer. The PRDM15 gene is of particular interest, given its low expression adult tissues overexpression B-cell lymphomas. Despite well characterized role stem biology during early development, the cancer remains obscure. Herein, we demonstrate that while largely dispensable for mouse somatic homeostasis...
RNA-sequencing (RNA-seq) is currently the leading technology for genome-wide transcript quantification. While volume of RNA-seq data rapidly increasing, publicly available provided mostly in raw form, with small portions processed non- uniformly. This mainly because computational demand, particularly alignment step, a significant barrier global and integrative retrospective analyses. To address this challenge, we developed all ChIP-seq sample signature search (ARCHS4), web resource that...
Abstract The NIH-funded LINCS Consortium is creating an extensive reference library of cell-based perturbation response signatures and sophisticated informatics tools incorporating a large number perturbagens, model systems, assays. To date, more than 350 datasets have been generated including transcriptomics, proteomics, epigenomics, cell phenotype competitive binding profiling volume variety data necessitate rigorous standards effective management modular processing pipelines end-user...