A5018043372- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- Single-cell and spatial transcriptomics
- Computational Drug Discovery Methods
- RNA and protein synthesis mechanisms
- Epigenetics and DNA Methylation
- Cancer-related molecular mechanisms research
- Genomics and Phylogenetic Studies
- RNA modifications and cancer
- Extracellular vesicles in disease
- RNA Research and Splicing
- Molecular Biology Techniques and Applications
- Ubiquitin and proteasome pathways
- Spaceflight effects on biology
- Microbial Metabolic Engineering and Bioproduction
- Viral-associated cancers and disorders
- DNA Repair Mechanisms
- Advanced Proteomics Techniques and Applications
- Cancer Genomics and Diagnostics
- Genomics and Chromatin Dynamics
- Radiation Therapy and Dosimetry
- MicroRNA in disease regulation
- Microtubule and mitosis dynamics
- Metabolism, Diabetes, and Cancer
- Cell Image Analysis Techniques
Auburn University
2023-2025
Vanderbilt University
2024-2025
Vanderbilt Health
2025
John F. Kennedy Center for the Performing Arts
2025
University of Nevada, Reno
2017-2024
Cho Ray Hospital
2024
Wayne State University
2011-2017
University of Toronto
2002-2015
University of New Brunswick
2008-2012
Canada Research Chairs
2006-2012
Abstract The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number possible combinations vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large combination dataset, consisting 11,576 experiments from 910 across 85 molecularly characterized cell lines, and results a DREAM Challenge evaluate computational strategies for...
Abstract A primary challenge in single-cell RNA sequencing (scRNA-seq) studies comes from the massive amount of data and excess noise level. To address this challenge, we introduce an analysis framework, named Decomposition using Hierarchical Autoencoder (scDHA), that reliably extracts representative information each cell. The scDHA pipeline consists two core modules. first module is a non-negative kernel autoencoder able to remove genes or components have insignificant contributions...
Advances in high-throughput technologies allow for measurements of many types omics data, yet the meaningful integration several different data remains a significant challenge. Another important and difficult problem is discovery molecular disease subtypes characterized by relevant clinical differences, such as survival. Here we present novel approach, called perturbation clustering subtyping (PINS), which able to address both challenges. The framework has been validated on thousands cancer...
Since cancer is a heterogeneous disease, tumor subtyping crucial for improved treatment and prognosis. We have developed subtype discovery tool, called PINSPlus, that is: (i) robust against noise unstable quantitative assays, (ii) able to integrate multiple types of omics data in single analysis (iii) dramatically superior established approaches identifying known subtypes novel subgroups with significant survival differences. Our validation on 12,158 samples from 44 datasets shows PINSPlus...
Abstract This manuscript describes the development of a resource module that is part learning platform named ‘NIGMS Sandbox for Cloud-based Learning’ (https://github.com/NIGMS/NIGMS-Sandbox). The delivers materials on Consensus Pathway Analysis in an interactive format uses appropriate cloud resources data access and analyses. analysis important because it allows us to gain insights into biological mechanisms underlying conditions. But availability many pathway methods, requirement coding...
ABSTRACT The EBNA1 protein of Epstein-Barr virus (EBV) is essential for EBV latent infection in ensuring the replication and stable segregation genomes activating transcription other latency genes. We have tested ability four host proteins (Brd2, Brd4, DEK, MeCP2) implicated papillomavirus Kaposi's sarcoma-associated herpesvirus to support EBNA1-mediated EBV-based plasmids Saccharomyces cerevisiae . found that Brd4 enabled while Brd2 MeCP2 had a general stimulatory effect on plasmid...
The minichromosome maintenance (MCM) complex, which plays multiple important roles in DNA replication, is loaded onto chromatin following mitosis, remains on until the completion of synthesis, and then unloaded by a poorly defined mechanism that involves MCM binding protein (MCM-BP). Here we show MCM-BP directly interacts with ubiquitin-specific protease USP7, this interaction occurs predominantly chromatin, can tether USP7 to proteins. Detailed biochemical structure analyses USP7-MCM-BP...
Post-translational modifications (PTMs) are critical regulators of protein function, and nearly 200 different types PTM have been identified. Advances in high-resolution mass spectrometry led to the identification an unprecedented number sites numerous organisms, potentially facilitating a more complete understanding how PTMs regulate cellular behavior. While databases created house resulting data, most these resources focus on individual PTM, do not consider quantitative analyses or provide...
Abstract Thioesterases are enzymes that hydrolyze thioester bonds in numerous biochemical pathways, for example fatty acid synthesis. This work reports known functions, structures, and mechanisms of updated thioesterase enzyme families, which classified into 35 families based on sequence similarity. Each family is at least one experimentally characterized enzyme, most have been crystallized their tertiary structure resolved. Classifying thioesterases allows to predict structures infer...
Breast cancer is the most common in world and second type of that causes death women. The timely accurate diagnosis breast using histopathological images crucial for patient care treatment. Pathologists can make more diagnoses with help a novel approach based on computer vision techniques. This an ensemble model two pretrained transformer models, namely, Vision Transformer (ViT) Data-Efficient Image (DeiT). ViTDeiT soft voting combines ViT DeiT model. proposed ViT-DeiT classifies...
ABSTRACT The Epstein-Barr virus (EBV) EBNA1 protein is important for the replication and mitotic segregation of EBV genomes in latently infected cells also activates transcription some viral latency genes. A Gly-Arg-rich region between amino acids 325 376 required both transcriptional activation functions EBNA1. Here we show that this modified by arginine methylation serine phosphorylation. Mutagenesis four potentially phosphorylated serines indicated phosphorylation multiple contributes to...
Minichromosome maintenance (MCM) complex replicative helicase complexes play essential roles in DNA replication all eukaryotes. Using a tandem affinity purification-tagging approach human cells, we discovered form of the MCM that contains previously unstudied protein, binding protein (MCM-BP). MCM-BP is conserved multicellular eukaryotes and shares limited homology with proteins. formed MCM3 to MCM7, which excluded MCM2; and, conversely, hexameric MCM2 MCM7 lacked MCM-BP, indicating can...
The PML tumor suppressor is the founding component of multiprotein nuclear structures known as bodies (PML-NBs), which control several cellular functions including apoptosis and antiviral effects. ubiquitin specific protease USP7 (also called HAUSP) to associate with PML-NBs be a tight binding partner two herpesvirus proteins that disrupt NBs. Here we investigated whether itself regulates PML-NBs. Silencing was found increase number PML-NBs, levels protein inhibit polyubiquitylation in...
Abstract In molecular biology and genetics, there is a large gap between the ease of data collection our ability to extract knowledge from these data. Contributing this fact that living organisms are complex systems whose emerging phenotypes results multiple interactions taking place on various pathways. This demands powerful yet user-friendly pathway analysis tools translate now abundant high-throughput into better understanding underlying biological phenomena. Here we introduce Consensus...
Unsupervised clustering of single-cell RNA sequencing data (scRNA-seq) is important because it allows us to identify putative cell types. However, the large number cells (up millions), high-dimensionality (tens thousands genes), and high dropout rates all present substantial challenges in analysis. Here we introduce a new method, named Clustering using Autoencoder Network fusion (scCAN), that can overcome these accurately segregate different types sparse scRNA-seq data. In an extensive...