Bingshan Li
Orcid: 0000-0003-2129-168X
According to our database1,
Bingshan Li
authored at least 17 papers
between 2014 and 2024.
Collaborative distances:
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Bibliography
2024
Leveraging generative AI to prioritize drug repurposing candidates for Alzheimer's disease with real-world clinical validation.
npj Digit. Medicine, 2024
Improving Genetic Perturbation Response Prediction with an Enhanced Biological Knowledge Graph.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024
2023
FAVOR: functional annotation of variants online resource and annotator for variation across the human genome.
Nucleic Acids Res., January, 2023
2022
TVAR: assessing tissue-specific functional effects of non-coding variants with deep learning.
Bioinform., October, 2022
A Bayesian framework to integrate multi-level genome-scale data for Autism risk gene prioritization.
BMC Bioinform., 2022
A computational framework to unify orthogonal information in DNA methylation and copy number aberrations in cell-free DNA for early cancer detection.
Briefings Bioinform., 2022
2021
DDIWAS: High-throughput electronic health record-based screening of drug-drug interactions.
J. Am. Medical Informatics Assoc., 2021
2020
DRAMS: A tool to detect and re-align mixed-up samples for integrative studies of multi-omics data.
PLoS Comput. Biol., 2020
Ultrasound Image-Based Diagnosis of Cirrhosis with an End-to-End Deep Learning model.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020
2019
De novo pattern discovery enables robust assessment of functional consequences of non-coding variants.
Bioinform., 2019
2017
Cancer driver gene discovery through an integrative genomics approach in a non-parametric Bayesian framework.
Bioinform., 2017
2016
BMC Bioinform., 2016
RVTESTS: an efficient and comprehensive tool for rare variant association analysis using sequence data.
Bioinform., 2016
Bioinform., 2016
2015
Bioinform., 2015
A haplotype-based framework for group-wise transmission/disequilibrium tests for rare variant association analysis.
Bioinform., 2015
2014
A gradient-boosting approach for filtering <i>de novo</i> mutations in parent-offspring trios.
Bioinform., 2014