A5068475876- Genomics and Rare Diseases
- Genomics and Phylogenetic Studies
- Cancer Genomics and Diagnostics
- Bioinformatics and Genomic Networks
- Metabolomics and Mass Spectrometry Studies
- Viral Infections and Immunology Research
- Gene expression and cancer classification
- CRISPR and Genetic Engineering
- Genetics, Bioinformatics, and Biomedical Research
- Gut microbiota and health
- Machine Learning in Bioinformatics
- Ruminant Nutrition and Digestive Physiology
- RNA and protein synthesis mechanisms
- Evolutionary Algorithms and Applications
Harvard University
2023-2025
Center for Systems Biology
2023-2025
University of California, San Francisco
2020
Clemson University
2018-2019
Abstract Computational methods for assessing the likely impacts of mutations, known as variant effect predictors (VEPs), are widely used in assessment and interpretation human genetic variation, well other applications like protein engineering. Many different VEPs have been released, there is tremendous variability their underlying algorithms, outputs, ways which methodologies predictions shared. This leads to considerable difficulties users trying navigate selection application VEPs. Here,...
The ability to alter genomes specifically by CRISPR-Cas gene editing has revolutionized biological research, biotechnology, and medicine. Broad therapeutic application of this technology, however, will require thorough preclinical assessment off-target homology-based prediction coupled with reliable methods for detecting editing. Several site nomination assays exist, but careful comparison is needed ascertain their relative strengths weaknesses. In study, HEK293T cells were treated...
Identifying causal mutations accelerates genetic disease diagnosis, and therapeutic development. Missense variants present a bottleneck in diagnoses as their effects are less straightforward than truncations or nonsense mutations. While computational prediction methods increasingly successful at for known genes, they do not generalize well to other genes the scores calibrated across proteome. To address this, we developed deep generative model, popEVE, that combines evolutionary information...
<title>Abstract</title> Identifying causal mutations accelerates genetic disease diagnosis, and therapeutic development. Missense variants present a bottleneck in diagnoses as their effects are less straightforward than truncations or nonsense mutations. While computational prediction methods increasingly successful at for <italic>known </italic>disease genes, they do not generalize well to other genes the scores calibrated across proteome<sup>1-6</sup>. To address this, we developed deep...
Given the complex relationship between gene expression and phenotypic outcomes, computationally efficient approaches are needed to sift through large high-dimensional datasets in order identify biologically relevant biomarkers. In this report, we describe a method of identifying most salient biomarker genes dataset, which call "candidate genes", by evaluating ability combinations classify samples from "classification potential". Our algorithm, Gene Oracle, uses neural network test user...
Ruminant animals have a symbiotic relationship with the microorganisms in their rumens. In this relationship, rumen microbes efficiently degrade complex plant-derived compounds into smaller digestible compounds, process that is very likely associated host animal feed efficiency. The resulting simpler metabolites can then be absorbed by and converted other enzymes. We used microbial community metabolic network inferred from shotgun metagenomics data to assess how system differs between are...
Abstract Genetic studies reveal extensive disease-associated variation across the human genome, predominantly in noncoding regions, such as promoters. Quantifying impact of these variants on disease risk is crucial to our understanding underlying mechanisms and advancing personalized medicine. However, current computational methods struggle capture variant effects, particularly those insertions deletions (indels), which can significantly disrupt gene expression. To address this challenge, we...