A5001438691- Computational Drug Discovery Methods
- Biomedical Text Mining and Ontologies
- Bioinformatics and Genomic Networks
- Tuberculosis Research and Epidemiology
- Genomics and Rare Diseases
- Animal testing and alternatives
- Advanced Graph Neural Networks
- vaccines and immunoinformatics approaches
- Pharmacogenetics and Drug Metabolism
- Synthesis and biological activity
- Machine Learning in Materials Science
- Animal Virus Infections Studies
- Identification and Quantification in Food
- Influenza Virus Research Studies
- Chemistry and Chemical Engineering
- SARS-CoV-2 and COVID-19 Research
- Machine Learning in Bioinformatics
- Advanced Sensor and Energy Harvesting Materials
- Hepatitis C virus research
- Dielectric materials and actuators
- Semantic Web and Ontologies
- Digital Imaging for Blood Diseases
- Insect and Pesticide Research
- Literature, Magical Realism, García Márquez
- Cancer-related gene regulation
University of North Carolina at Chapel Hill
2015-2025
University of Pennsylvania
2023
Purdue University West Lafayette
2021
Background: Modern chemical toxicology is facing a growing need to Reduce, Refine, and Replace animal tests (Russell 1959) for hazard identification. The most common type of assays acute toxicity assessment chemicals used as pesticides, pharmaceuticals, or in cosmetic products known “6-pack” battery tests, including three topical (skin sensitization, skin irritation corrosion, eye corrosion) systemic (acute oral toxicity, inhalation dermal toxicity) end points. Methods: We compiled, curated,...
Abstract The main protease (M pro ) of the SARS‐CoV‐2 has been proposed as one major drug targets for COVID‐19. We have identified experimental data on inhibitory activity compounds tested against closely related (96 % sequence identity, 100 active site conservation) M SARS‐CoV. developed QSAR models these inhibitors and employed virtual screening all drugs in DrugBank database. Similarity searching molecular docking were explored parallel, but failed to correctly discriminate between...
Multiple approaches to quantitative structure–activity relationship (QSAR) modeling using various statistical or machine learning techniques and different types of chemical descriptors have been developed over the years. Oftentimes models are used in consensus make more accurate predictions at expense model interpretation. We propose a simple, fast, reliable method termed Multi-Descriptor Read Across (MuDRA) for developing both interpretable models. The is conceptually related well-known kNN...
Computational approaches to support rare disease diagnosis are challenging build, requiring the integration of complex data types such as ontologies, gene-to-phenotype associations, and cross-species into variant gene prioritisation algorithms (VGPAs). However, performance VGPAs has been difficult measure is impacted by many factors, for example, ontology structure, annotation completeness or changes underlying algorithm. Assertions capabilities often not reproducible, in part because there...
Small, colloidally aggregating molecules (SCAMs) are the most common source of false positives in high-throughput screening (HTS) campaigns. Although SCAMs can be experimentally detected and suppressed by addition detergent assay buffer, sensitivity is not routinely monitored HTS. Computational methods thus needed to flag potential during HTS triage. In this study, we have developed rigorously validated quantitative structure-interference relationship (QSIR) models detergent-sensitive...
Computational approaches to support rare disease diagnosis are challenging build, requiring the integration of complex data types such as ontologies, gene-to-phenotype associations, and cross-species into variant gene prioritisation algorithms (VGPAs). However, performance VGPAs has been difficult measure is impacted by many factors, for example, ontology structure, annotation completeness or changes underlying algorithm. Assertions capabilities often not reproducible, in part because there...
Abstract Summary Knowledge graphs are being increasingly used in biomedical research to link large amounts of heterogenous data and facilitate reasoning across diverse knowledge sources. Wider adoption exploration the community is limited by requirements understand underlying graph structure terms entity types relationships, represented as nodes edges, respectively, learn specialized query languages for mining exploration. We have developed a user-friendly interface dubbed ExEmPLAR...
In response to the COVID-19 pandemic, we established COVID-KOP, a new knowledgebase integrating existing Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways (ROBOKOP) biomedical knowledge graph with information from recent literature on annotated CORD-19 collection. COVID-KOP can be used effectively generate hypotheses concerning repurposing of known drugs and clinical drug candidates against by establishing respective confirmatory pathways action.COVID-KOP is freely...
The outbreak of a novel human coronavirus (SARS-CoV-2) has evolved into global health emergency, infecting hundreds thousands people worldwide. We have identified experimental data on the inhibitory activity compounds tested against closely related (96% sequence identity, 100% active site conservation) protease SARS-CoV and employed this to build QSAR models for dataset. these virtual screening all drugs from DrugBank, including in clinical trials. Molecular docking similarity search...
Many laboratories working in the field of drug discovery use ZINC database to identify and then acquire commercially available chemicals. However, finding best deal for a given compound is often time-intensive laborious, as process involves searching all vendors selling desired compound, comparing prices, interacting with preferred vendor. To streamline this process, we have developed Express, web application that simplifies online purchase chemicals annotated database. For any known ID,...
The outbreak of a novel human coronavirus (SARS-CoV-2) has evolved into global health emergency, infecting hundreds thousands people worldwide. We have identified experimental data on the inhibitory activity compounds tested against closely related (96% sequence identity, 100% active site conservation) protease SARS-CoV and employed this to build QSAR models for dataset. these virtual screening all drugs from DrugBank, including in clinical trials. Molecular docking similarity search...
<p>In response to the COVID-19 pandemic, we established COVID-KOP, a new knowledgebase integrating existing ROBOKOP biomedical knowledge graph with information from recent literature on annotated in CORD-19 collection. COVID-KOP can be used effectively test hypotheses concerning repurposing of known drugs and clinical drug candidates against COVID-19. is freely accessible at <a href="https://covidkop.renci.org/">https://covidkop.renci.org/</a>. For code instructions for...
Abstract In the United States, a pre-market regulatory submission for any medical device that comes into contact with either patient or clinical practitioner must include an adequate toxicity evaluation of chemical substances can be released from during its intended use. These substances, also referred to as extractables and leachables, evaluated their potential induce sensitization/allergenicity, which traditionally has been done in animal assays such guinea pig maximization test (GPMT)....
Knowledge-graph (KG) embeddings have emerged as a promise in addressing challenges faced by modern biomedical research, including the growing gap between therapeutic needs and available treatments. The popularity of KG graph analytics is on rise, due at least partially to presumed semanticity learned embeddings. Unfortunately, ability node neighborhood picked up an embedding capture node's semantics may depend characteristics data. One reasons for this problem that nodes can be promiscuous,...
Diseases caused by new viruses costs thousands if not millions of human lives and trillions dollars in damage to the global economy. Despite rapid development vaccines for SARS-CoV-2, lack small molecule antiviral drugs that work against multiple viral families (broad-spectrum antivirals; BSAs) has left entire world’s population vulnerable infection between beginning outbreak widespread availability vaccines. Developing BSAs is an attractive, yet challenging, approach could prevent next,...
The COVID-19 pandemic has catalyzed a widespread effort to identify drug candidates and biological targets of relevance SARS-COV-2 infection, which resulted in large numbers publications on this subject. We have built the Knowledge Extractor (COKE), web application extract, curate, annotate essential drug–target relationships from research literature COVID-19. SciBiteAI ontological tagging COVID Open Research Data set (CORD-19), repository scientific publications, was employed relationships....
<p><a>Since 2009, animal testing for cosmetic products has been prohibited in Europe, and 2016, US EPA announced their intent to modernize the so-called "6-pack" of acute toxicity tests (acute oral toxicity, dermal inhalation skin irritation corrosion, eye sensitization) expand acceptance alternative methods reduce pesticides. We have compiled, curated, integrated largest publicly available dataset developed an ensemble QSAR models all six endpoints. All were validated according...
Since 2009, animal testing for cosmetic products has been prohibited in Europe, and 2016, US EPA announced their intent to modernize the so-called "6-pack" of acute toxicity tests (acute oral toxicity, dermal inhalation skin irritation corrosion, eye sensitization) expand acceptance alternative methods reduce pesticides. We have compiled, curated, integrated largest publicly available dataset developed an ensemble QSAR models all six endpoints. All were validated according OECD principles...