A5042634777- Cell Image Analysis Techniques
- Bioinformatics and Genomic Networks
- Gene Regulatory Network Analysis
- 3D Printing in Biomedical Research
- Computational Drug Discovery Methods
- Single-cell and spatial transcriptomics
- Receptor Mechanisms and Signaling
- Genomics and Chromatin Dynamics
- AI in cancer detection
- Cellular Mechanics and Interactions
- Cancer, Stress, Anesthesia, and Immune Response
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
- Adenosine and Purinergic Signaling
- Machine Learning in Bioinformatics
- Gene expression and cancer classification
- Protein Hydrolysis and Bioactive Peptides
- Data Visualization and Analytics
- Radiomics and Machine Learning in Medical Imaging
- Genetics, Aging, and Longevity in Model Organisms
- RNA Research and Splicing
- Microbial Metabolic Engineering and Bioproduction
- Scientific Computing and Data Management
- Biomedical Text Mining and Ontologies
- Artificial Intelligence in Healthcare and Education
The University of Texas Southwestern Medical Center
2016-2025
Southwestern Medical Center
2017-2022
University of Pittsburgh
2013-2019
Accelerated Medical Diagnostics (United States)
2016
Discovery Institute
2014
Sabancı Üniversitesi
2009-2013
Quantitative analysis of known drug–target interactions emerged in recent years as a useful approach for drug repurposing and assessing side effects. In the present study, we method that uses probabilistic matrix factorization (PMF) this purpose, which is particularly analyzing large interaction networks. DrugBank drugs clustered based on PMF latent variables show phenotypic similarity even absence 3D shape similarity. Benchmarking computations outperforms those recently introduced provided...
Human dopamine (DA) transporter (hDAT) regulates dopaminergic signaling in the central nervous system by maintaining synaptic concentration of DA at physiological levels, upon reuptake into presynaptic terminals. translocation involves co-transport two sodium ions and channeling a chloride ion, it is achieved via alternating access between outward-facing (OF) inward-facing states DAT. hDAT target for addictive drugs, such as cocaine, amphetamine (AMPH), therapeutic antidepressants. Our...
α1-Antitrypsin deficiency (ATD) is a common genetic disorder that can lead to end-stage liver and lung disease. Although transplantation remains the only therapy currently available, manipulation of proteostasis network (PN) by small molecule therapeutics offers great promise. To accelerate drug-discovery process for this disease, we first developed semi-automated high-throughput/content-genome-wide RNAi screen identify PN modifiers affecting accumulation α1-antitrypsin Z mutant (ATZ) in...
Abstract Immune checkpoint blockade (ICB) therapies work by disrupting inhibitory signals that dampen T-cell activation, thus rejuvenating tumor-specific T cells. While ICB has shown durable responses in some patients, a significant number do not benefit, underscoring the need to explore additional mechanisms. The modulation of immune neurotransmitters (NTs) been studied various disease settings context multiple receptors, including adrenergic dopaminergic and cholinergic receptors. NT...
Every biological experiment requires a choice of throughput balanced against physiological relevance. Most primary drug screens neglect critical parameters such as microenvironmental conditions, cell-cell heterogeneity, and specific readouts cell fate for the sake throughput. Here we describe methodology to quantify proliferation viability single cells in 3D culture conditions by leveraging automated microscopy image analysis facilitate reliable high-throughput measurements. We detail...
Abstract Summary: BalestraWeb is an online server that allows users to instantly make predictions about the potential occurrence of interactions between any given drug–target pair, or predict most likely interaction partners drug target listed in DrugBank. It also permits identify similar drugs targets based on their patterns. Outputs help develop hypotheses repurposing as well side effects. Availability and implementation: accessible at http://balestra.csb.pitt.edu/ . The tool built using a...
The classical form of α1-antitrypsin deficiency (ATD) is characterized by intracellular accumulation the misfolded variant Z (ATZ) and severe liver disease in some affected individuals. In this study, we investigated possibility discovering novel therapeutic agents that would reduce ATZ interrogating a C. elegans model ATD with high-content genome-wide RNAi screening computational systems pharmacology strategies. was utilized to identify genes modify pipeline developed make high confidence...
Alexander, John C. MD, MBA; Romito, Bryan T. Çobanoğlu, Murat Can PhD Author Information
Purpose To develop a custom deep convolutional neural network (CNN) for noninvasive prediction of breast cancer nodal metastasis. Materials and Methods This retrospective study included patients with newly diagnosed primary invasive known pathologic (pN) clinical (cN) status who underwent dynamic contrast-enhanced (DCE) MRI at the authors' institution between July 2013 2016. Clinicopathologic data (age, estrogen receptor human epidermal growth factor 2 status, Ki-67 index, tumor grade) cN pN...
The classification of G-Protein Coupled Receptor (GPCR) sequences is an important problem that arises from the need to close gap between large number orphan receptors and relatively small annotated receptors. Equally characterization GPCR Class A subfamilies gaining insight into ligand interaction since encompasses a very drug-targeted In this work, we propose method for subfamily using sequence-derived motifs which characterizes by discovering receptor-ligand sites. best characterize are...
Quantitative Systems Pharmacology (QSP) is a drug discovery approach that integrates computational and experimental methods in an iterative way to gain comprehensive, unbiased understanding of disease processes inform effective therapeutic strategies. We report the implementation QSP Huntington's Disease, with application chemogenomics platform identify strategies protect neuronal cells from mutant huntingtin induced death. Using STHdh Q111 cell model, we investigated protective effects...
Norepinephrine is a key sympathetic neurotransmitter, which acts to suppress CD8 + T cell cytokine secretion and lytic activity by signaling through the β2-adrenergic receptor (ADRB2). Although ADRB2 considered generally immunosuppressive, its role in regulating differentiation of effector cells response infection has not been investigated. Using an adoptive transfer approach, we compared expansion wild type (WT) Adrb2 -/- throughout primary vesicular stomatitis virus (VSV) vivo . We...
Abstract Motivation Activity of transcriptional regulators is crucial in elucidating the mechanism phenotypes. However regulatory activity hypotheses are difficult to experimentally test. Therefore, we need accurate and reliable computational methods for regulator inference. There extensive work this area, however, current have difficulty with one or more following: resolving TFs overlapping regulons, reflecting known relationships, flexible modeling TF over regulon. Results We present...
Abstract Background Every biological experiment requires a choice of throughput balanced against physiological relevance. Most primary drugs screens neglect critical parameters such as microenvironmental conditions, cell-cell heterogeneity, and specific readouts cell fate for the sake throughput. Methods Here we describe methodology to quantify proliferation viability single cells in 3D culture conditions by leveraging automated microscopy image analysis facilitate reliable high-throughput...
Abstract We propose a novel strategy for incorporating hierarchical supervised label information into nonlinear dimensionality reduction techniques. Specifically, we extend t-SNE, UMAP, and PHATE to include known or predicted class labels demonstrate the efficacy of our approach on multiple single-cell RNA sequencing datasets. Our approach, “Haisu,” is applicable across domains methods reduction. In general, mathematical effect Haisu can be summarized as variable perturbation high...
We propose a novel strategy for incorporating hierarchical supervised label information into nonlinear dimensionality reduction techniques. Specifically, we extend t-SNE, UMAP, and PHATE to include known or predicted class labels demonstrate the efficacy of our approach on multiple single-cell RNA sequencing datasets. Our approach, "Haisu," is applicable across domains methods reduction. In general, mathematical effect Haisu can be summarized as variable perturbation high dimensional space...
Abstract The heterogeneity of cancer necessitates developing a multitude targeted therapies. We propose the view that drug discovery is low rank tensor completion problem. implement this vision by using heterogeneous public data to construct drug-target-disease associations. show validity approach computationally simulations, and experimentally testing candidates. Specifically, we novel candidate, SU11652, controls melanoma tumor growth, including BRAF WT melanoma. Independently, another...