Weizhong Li, PhD

Professor
858-750-4041

Weizhong Li is a professor at the J. Craig Venter Institute working in the informatics group. Dr. Li’s research is focused on the development of algorithms and computational resources in solving data analysis problems in genomics, metagenomics, RNA-seq and other next generation sequencing data and other omics data. He is currently focused on using his expertise to better quantify and understand the human microbiome in the gut and oral cavities.

Prior to joining JCVI, Dr. Li was a senior principal scientist at Human Longevity Inc., a research scientist and investigator at University of California San Diego, a staff scientist at Sanford Burnham Prebys Medical Discovery Institute and a senior research scientist at Quorex Pharmaceuticals. He received his PhD and his BS in computational chemistry from the Nankai University in China.

Research Priorities

Computational tool development
  • Ultra-fast and robust algorithms in biological sequence clustering analysis (CD-HIT), applications using clustering algorithms in various areas such as 16S rRNA analysis and improving NGS data analysis.
  • Algorithms, methods and integrated pipelines for metagenomics including mapping, assembly, visualization, taxonomy identification and functional annotation.
  • Computer cloud-based workflows and web portal for end-to-end RNA-seq sequence data analysis.
Metagenomics and microbiome
  • Microbiome disease association through large-scale metagenomic sequencing projects for various disease types, such as IBD, liver disease, diabetes, infection and so on.
  • Host-microbiome study for human and animals using multi-omics approach involving host genomics data, RNA-seq, 16S and metagenomics data.

Publications

Li W, Tapiainen T, Brinkac L, Lorenzi HA, Moncera K, Tejesvi M, Salo J, Nelson KE
Vertical transmission of gut microbiome and antimicrobial resistance genes in infants exposed to antibiotics at birth.
The Journal of infectious diseases. 2020-04-02;
PMID: 32239170
Pessoa L, Aleti G, Choudhury S, Nguyen D, Yaskell T, Zhang Y, Li W, Nelson KE, Neto LLS, Sant'Ana ACP, Freire M
Host-Microbial Interactions in Systemic Lupus Erythematosus and Periodontitis.
Frontiers in immunology. 2019-11-12; 10.2602.
PMID: 31781106
Visconti A, Le Roy CI, Rosa F, Rossi N, Martin TC, Mohney RP, Li W, de Rinaldis E, Bell JT, Venter JC, Nelson KE, Spector TD, Falchi M
Interplay between the human gut microbiome and host metabolism.
Nature communications. 2019-10-03; 10.1: 4505.
PMID: 31582752
Loomba R, Seguritan V, Li W, Long T, Klitgord N, Bhatt A, Dulai PS, Caussy C, Bettencourt R, Highlander SK, Jones MB, Sirlin CB, Schnabl B, Brinkac L, Schork N, Chen CH, Brenner DA, Biggs W, Yooseph S, Venter JC, Nelson KE
Gut Microbiome-Based Metagenomic Signature for Non-invasive Detection of Advanced Fibrosis in Human Nonalcoholic Fatty Liver Disease.
Cell metabolism. 2017-05-02; 25.5: 1054-1062.e5.
PMID: 28467925
Greenwald WW, Klitgord N, Seguritan V, Yooseph S, Venter JC, Garner C, Nelson KE, Li W
Utilization of defined microbial communities enables effective evaluation of meta-genomic assemblies.
BMC genomics. 2017-04-13; 18.1: 296.
PMID: 28407798
Li W, Richter RA, Jung Y, Zhu Q, Li RW
Web-based bioinformatics workflows for end-to-end RNA-seq data computation and analysis in agricultural animal species.
BMC genomics. 2016-09-27; 17.1: 761.
PMID: 27678198
Anderson EL, Li W, Klitgord N, Highlander SK, Dayrit M, Seguritan V, Yooseph S, Biggs W, Venter JC, Nelson KE, Jones MB
A robust ambient temperature collection and stabilization strategy: Enabling worldwide functional studies of the human microbiome.
Scientific reports. 2016-08-25; 6.31731.
PMID: 27558918
Zhu Z, Niu B, Chen J, Wu S, Sun S, Li W
MGAviewer: a desktop visualization tool for analysis of metagenomics alignment data.
Bioinformatics (Oxford, England). 2013-01-01; 29.1: 122-3.
PMID: 23044549
Fu L, Niu B, Zhu Z, Wu S, Li W
CD-HIT: accelerated for clustering the next-generation sequencing data.
Bioinformatics (Oxford, England). 2012-12-01; 28.23: 3150-2.
PMID: 23060610
Li W, Fu L, Niu B, Wu S, Wooley J
Ultrafast clustering algorithms for metagenomic sequence analysis.
Briefings in bioinformatics. 2012-11-01; 13.6: 656-68.
PMID: 22772836
Wu S, Zhu Z, Fu L, Niu B, Li W
WebMGA: a customizable web server for fast metagenomic sequence analysis.
BMC genomics. 2011-09-07; 12.444.
PMID: 21899761
Niu B, Zhu Z, Fu L, Wu S, Li W
FR-HIT, a very fast program to recruit metagenomic reads to homologous reference genomes.
Bioinformatics (Oxford, England). 2011-06-15; 27.12: 1704-5.
PMID: 21505035
Niu B, Fu L, Sun S, Li W
Artificial and natural duplicates in pyrosequencing reads of metagenomic data.
BMC bioinformatics. 2010-04-13; 11.187.
PMID: 20388221
Huang Y, Niu B, Gao Y, Fu L, Li W
CD-HIT Suite: a web server for clustering and comparing biological sequences.
Bioinformatics (Oxford, England). 2010-03-01; 26.5: 680-2.
PMID: 20053844
Li W
Analysis and comparison of very large metagenomes with fast clustering and functional annotation.
BMC bioinformatics. 2009-10-28; 10.359.
PMID: 19863816
Huang Y, Gilna P, Li W
Identification of ribosomal RNA genes in metagenomic fragments.
Bioinformatics (Oxford, England). 2009-05-15; 25.10: 1338-40.
PMID: 19346323
Li W, Wooley JC, Godzik A
Probing metagenomics by rapid cluster analysis of very large datasets.
PloS one. 2008-01-01; 3.12: e3375.
PMID: 18846219
Li W, Godzik A
Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences.
Bioinformatics (Oxford, England). 2006-07-01; 22.13: 1658-9.
PMID: 16731699

Research Priorities

Computational tool development
  • Ultra-fast and robust algorithms in biological sequence clustering analysis (CD-HIT), applications using clustering algorithms in various areas such as 16S rRNA analysis and improving NGS data analysis.
  • Algorithms, methods and integrated pipelines for metagenomics including mapping, assembly, visualization, taxonomy identification and functional annotation.
  • Computer cloud-based workflows and web portal for end-to-end RNA-seq sequence data analysis.
Metagenomics and microbiome
  • Microbiome disease association through large-scale metagenomic sequencing projects for various disease types, such as IBD, liver disease, diabetes, infection and so on.
  • Host-microbiome study for human and animals using multi-omics approach involving host genomics data, RNA-seq, 16S and metagenomics data.

Chronic Wound Microbiome

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Gut Microbiome-Based Metagenomic Signature for Detection of Advanced Fibrosis in Nonalcoholic Fatty Liver Disease

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