Kai Ye
Professor at Xi'an Jiaotong University
Xi'an, Shaanxi, China
Summary
👤
Senior🎓
Top SchoolKai Ye is a Professor and computational biologist with 13+ years of experience developing scalable pattern-growth algorithms and data-mining methods for DNA and protein sequence analysis. His work spans academia and research institutes—including Xi'an Jiaotong University, Washington University Genome Institute, Leiden University, and EMBL-EBI—focusing on omics informatics and medical genomics. He originated tools and methods such as Pindel for detecting structural variants from paired-end reads and multiple pattern-growth approaches for motif, hairpin and unique-string discovery across genomes. Trained as a PhD in Biopharmaceutical Science, he combines quantitative pharmacology modeling, homology modeling and docking with machine-learning feature-weighting approaches for specificity prediction. Beyond algorithm design he has hands-on wet-lab experience from vaccine and protein expression projects, giving him uncommon breadth across computational and experimental biology. Colleagues describe him as a method-builder who turns biological insight into efficient, reusable computational tools.
13 years of coding experience
7 years of employment as a software developer
B.Sc. and M.Sc. of Biopharmaceutical science, Biopharmaceutical science, B.Sc. and M.Sc. of Biopharmaceutical science, Biopharmaceutical science at Wuhan UniversityDoctor of Philosophy (PhD), Biopharmaceutical science, Doctor of Philosophy (PhD), Biopharmaceutical science at Leiden UniversityMiddle school, general, Middle school, general at No. 11 middle school in Wuhan China
Chinese
Github Skills (13)
bioinformatics10
tandem10
sequence10
breakpoints10
pattern10
medium10
sequencing10
normal10
bioconda8
pipeline1
genomics1
genome1
insertion1
Programming languages (2)
Github contributions (4)
genome/pindel
Apr 2013 - Aug 2016
Pindel can detect breakpoints of large deletions, medium sized insertions, inversions, tandem duplications and other structural variants at single-based resolution from next-gen sequence data. It uses a pattern growth approach to identify the breakpoints of these variants from paired-end short reads.
Contributions:140 commits, 1 PR, 27 pushes in 3 years 4 months
sequencetandembioinformaticsbreakpointsgen
ding-lab/msisensor
May 2014 - Jan 2021
microsatellite instability detection using tumor only or paired tumor-normal data
Contributions:11 commits, 9 pushes, 7 comments in 6 years 9 months
normalmicrosatellitetumor
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