Faculty profile
Yong Gao
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Research
Latest papers
Beaconet: A Reference-Free Method for Integrating Multiple Batches of Single-Cell Transcriptomic Data in Original Molecular Space.
Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
CCIP: predicting CTCF-mediated chromatin loops with transitivity.
Bioinformatics (Oxford, England) · 2021 · senior author
Improving Single-Cell RNA-seq Clustering by Integrating Pathways.
Briefings in bioinformatics · 2021 · senior author
Latest funding
- $138,000
Artificial Intelligence and Network Science: Solution Concepts, Graph-Theoretic Characterizations, and Their Societal Aspects
NSERC · 2019 · Principal investigator
- $160,000
Computational Problems in Artificial Intelligence and Network Science: Probabilistic Analyses, Graph-Theoretic Characterizations, and Algorithmic Solutions
NSERC · 2014 · Principal investigator
- $95,000
Algorithms and complexity of hard problems: bridging the gap between theory and practice
NSERC · 2009 · Principal investigator
5 publications.
Beaconet: A Reference-Free Method for Integrating Multiple Batches of Single-Cell Transcriptomic Data in Original Molecular Space.
Xu H, Ye Y, Duan R, Gao Y, Hu Y, Gao L
CCIP: predicting CTCF-mediated chromatin loops with transitivity.
Wang W, Gao L, Ye Y, Gao Y
Improving Single-Cell RNA-seq Clustering by Integrating Pathways.
Zhang C, Gao L, Wang B, Gao Y
Evaluation and comparison of multi-omics data integration methods for cancer subtyping.
Duan R, Gao L, Gao Y, Hu Y, Xu H, Huang M, Song K, Wang H, Dong Y, Jiang C, Zhang C, Jia S
Anti-triangle centrality-based community detection in complex networks.
Jia S, Gao L, Gao Y, Wang H
Artificial Intelligence and Network Science: Solution Concepts, Graph-Theoretic Characterizations, and Their Societal Aspects
Principal investigators: Gao, Yong
Keywords: abstract argumentation and declarative problem solving; artificial intelligence; fair solutions in algorithmic decision making; graph algorithms and general-purpose algorithms; meso-scale organization of complex networks; network communities and graph classes; network science; probabilistic and empirical analyses of algorithmic problems; random graphs and probabilistic models of complex networks; solution concepts in reasoning and problem solving
Computational Problems in Artificial Intelligence and Network Science: Probabilistic Analyses, Graph-Theoretic Characterizations, and Algorithmic Solutions
Principal investigators: Gao, Yong
Algorithms and complexity of hard problems: bridging the gap between theory and practice
Principal investigators: Gao, Yong
Algorithms, heuristics and typical case complexity of hard problems
Principal investigators: Gao, Yong
From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.
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