MO
Matthew O'Meara
Assistant Professor Department of Computational Medicine and Bioinformatics, University of Michigan (Bioinformatics and computational biology not elsewhere classified; Infectious diseases; Pharmacology and pharmaceutical sciences not elsewhere classified; Biostatistics)
Ann Arbor, Michigan, United States
Publications
- https://maomlab.github.io/
- Ligand Similarity Complements Sequence, Physical Interaction, and Co-Expression for Gene Function Prediction
- Global proteomic analyses define an environmentally contingent Hsp90 interactome and reveal chaperone-dependent regulation of stress granule proteins and the R2TP complex in a fungal pathogen
- A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing
- A SARS-CoV-2 protein interaction map reveals targets for drug repurposing
- Reengineering biocatalysts: Computational redesign of chondroitinase ABC improves efficacy and stability
- DeORFanizing Candida albicans Genes using Coexpression
- Phospholipidosis is a shared mechanism underlying the in vitro antiviral activity of many repurposed drugs against SARS-CoV-2
- Valproic Acid-Induced Changes of 4D Nuclear Morphology in Astrocyte Cells
- Crystal structures of the σ2 receptor template large-library docking for selective chemotypes active in vivo
- Drug-induced phospholipidosis confounds drug repurposing for SARS-CoV-2
- A Multi-Omics Human Liver Organoid Screening Platform for DILI Risk Prediction
- Structures of the σ2 receptor enable docking for bioactive ligand discovery
- Scientific benchmarks for guiding macromolecular energy function improvement
- Role of electrostatic repulsion in controlling pH-dependent conformational changes of viral fusion proteins.
- The Cryptococcus neoformans Rim101 transcription factor directly regulates genes required for adaptation to the host.
- Combined covalent-electrostatic model of hydrogen bonding improves structure prediction with Rosetta.
- A Web Resource for Standardized Benchmark Datasets, Metrics, and Rosetta Protocols for Macromolecular Modeling and Design.
- The Recognition of Identical Ligands by Unrelated Proteins.
- The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design.
- Prediction of enzymatic pathways by integrative pathway mapping.
- High-Throughput Screening Identifies Genes Required for Candida albicans Induction of Macrophage Pyroptosis.
- Local delivery of stabilized chondroitinase ABC degrades chondroitin sulfate proteoglycans in stroke-injured rat brains.
- Ultra-large library docking for discovering new chemotypes.
- A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments
- Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms.
- Property-Unmatched Decoys in Docking Benchmarks.
- Morphological cell profiling of SARS-CoV-2 infection identifies drug repurposing candidates for COVID-19.
- Chondroitinase ABC Mutants and Methods of Manufacture and use Thereof
- Leveraging machine learning essentiality predictions and chemogenomic interactions to identify antifungal targets.
- Prioritizing virtual screening with interpretable interaction fingerprints
- In Vitro Evaluation and Mitigation of Niclosamide’s Liabilities as a COVID-19 Treatment
- Prioritizing Virtual Screening with Interpretable Interaction Fingerprints
- Human commensal Candida albicans strains demonstrate substantial within-host diversity and retained pathogenic potential
- Multiple ParA/MinD ATPases Coordinate the Positioning of Disparate Cargos in a Bacterial Cell
- In Vitro Evaluation and Mitigation of Niclosamide's Liabilities as a COVID-19 Treatment.
- Maximum geodesic routing in the plane with obstacles
- Colour Patterns for Polychromatic Four-colourings of Rectangular Subdivisions
- DeORFanizing Candida albicans Genes using Co-Expression
- Development of an Automated Screen for Kv7.2 Potassium Channels and Discovery of a New Agonist Chemotype
- Multiple ParA/MinD ATPases coordinate the positioning of disparate cargos in a bacterial cell
- Erratum: The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design (J. Chem. Theory Comput. (2017) 13: 6 (3031-3048) DOI: 10.1021/acs.jctc.7b00125)
- Development of an automated screen for Kv7.2 potassium channels and discovery of a new agonist chemotype
- Valproic acid-induced changes of 4D nuclear morphology in astrocyte cells
- The Rosetta all-atom energy function for macromolecular modeling and design
- Morphological Cell Profiling of SARS-CoV-2 Infection Identifies Drug Repurposing Candidates for COVID-19.
- Computational Redesign of Bacterial Chondroitinase ABC to Treat Spinal Cord Injury and Stroke
- Phospholipidosis explains a plurality of SARS-CoV-2 Drug-repurposing hits
- CADs as a target for chemoinformatic filtering in virtual screening libraries
- Designer proteins for nerve regeneration
- From Protein-Interactions to Organoids: Drug Repurposing for SARS-CoV-2
- From millions of images of SARS-CoV-2 infected cells to drug mechanism of action
- Property-unmatched decoys in docking benchmarks and bootstrapping on the ranked list to obtain confidence intervals
- Machine Learning and Assay Development for Image-based Phenotypic Profiling of Drug Treatments
- The life and times of endogenous opioid peptides: Updated understanding of synthesis, spatiotemporal dynamics, and the clinical impact in alcohol use disorder.
- Morphological cell profiling of SARS-CoV-2 infection identifies lactoferrin as candidate for COVID-19
- A metabolic code for polypharmacology
- A Hydrogen Bonding Geometry Encyclopedia
- A Hydrogen Bonding Geometry Encyclopedia
- A metabolic code for polypharmacology
- Testing the predictive limits of large scale virtual screening
- Host-pathogen interactions of highly pathogenic coronaviruses reveal drug targets
- A metabolic code for pharmacology
- A Human Liver Organoid Screening Platform for DILI Risk Prediction
- Virtual Phospholipidosis explains a plurality of SARS-CoV-2 Drug-repurposing hits
- High-Content Screening to Identify Inhibitors of Dengue Virus Replication
- Imaging-based screening identifies modulators of theeIF3translation initiation factor complex inCandida albicans