Christopher M. Taylor, PhD

Associate Professor
Department of Microbiology, Immunology & Parasitology
Bioinformatics, Biostatistics, & Computational Biology Core
Louisiana Biomedical Research Network

533 Bolivar Street, Room 605
New Orleans, LA 70112



Ph.D. in Computer Science
Algorithmic Analysis of Human DNA Replication Timing
University of Virginia, Charlottesville, VA - 2008

M.S. in Computer Science
A Mathematical Model for Knowledge Acquisition
University of Virginia, Charlottesville, VA - 2002

B.S. with Honors in Computer Science and Mathematics
University of Mary Washington, Fredericksburg, VA - 2000



Dr. Taylor earned his PhD in 2008 from the University of Virginia under the direction of Dr. Anindya Dutta (Harry F. Byrd Professor and Chair of Biochemistry and Molecular Genetics) and Dr. Gabriel Robins (Professor of Computer Science). For his dissertation, Dr. Taylor developed a method for generating a continuous profile of DNA replication timing from discrete pools of replicated DNA hybridized to genome tiling microarrays. This work also proposed a method for finding origins of replication and discovering regions of the genome where alleles replicate asynchronously. This approach was presented at Pattern Recognition in Bioinformatics 2008 in Melbourne, Australia and later published as part of an invited chapter for Methods in Molecular Biology in 2009. During this time, Dr. Taylor was a member of the NIH ENCODE Consortium and a member of the Chromatin, Chromosomes & Replication Analysis group as part of the ENCODE Science publication. He was also the lead analyst for replication and a member of the Integrated Analysis and Manuscript Preparation group for the ENCODE Nature publication.

After his graduate work, Dr. Taylor joined the University of New Orleans as an Assistant Professor of Computer Science in 2008. As a new faculty member, Dr. Taylor shifted his focus from microarrays to the emerging technology of high throughput sequencing. He established several collaborations with basic scientists and clinical researchers in the area and developed two major branches of his subsequent research:  Microbial Community Sequencing and RNA Sequencing. This work led to the development of PARSES and RNA CoMPASS, integrated systems for dual RNA-Sequencing analysis along with a software framework for microbial community profiling.

Dr. Taylor joined LSUHSC in December 2012 as an Associate Professor in the Department of Microbiology, Immunology and Parasitology where he currently resides. He is a founding member of the Microbial Genomics Resource Group and has built an informatics laboratory at the School of Medicine focused on microbial community sequencing, analysis, and visualization. He was appointed in July 2016 as the Director of the Bioinformatics, Biostatistics and Computational Biology Core of the Louisiana Biomedical Research Network and was awarded Tenure from LSUHSC in 2017. Dr. Taylor co-organizes an annual conference on bioinformatics and computational biology for the LBRN and his research laboratory maintains several terabytes of sequence data and designs innovative software systems for visualization and analysis of high-throughput sequencing experiments.


Clinical Interests

Dr. Taylor's lab has a strong interest in the interaction between reproductive tract microbiota and sexually transmitted infections.  He was awarded a Multi-PI R01 from NIH/NIAID in August 2017 to study the consequences of vaginal microbiota on IFNγ mediated clearance of Chlamydia infections.  Hi is also closely involved as a co-invesigator with an NIH/NIAID R01 funded in January 2020 to study the relationship of STI screening with adverse birth and newborn outcomes. He is a co-investigator studying the releationship between vaginal microbiota and biofilm formation in bacterial vaginosis on an NIH/NIAID R01 that was funded in February 2020 which is following changes in the vaginal microbiota over the course of time. Dr. Taylor also has clinical interests in the use of shotgun metagenomic sequencing of the reproductive tract microbiota to identify pathogens and direct targetted treatment of STIs.


Research Interests

Dr. Taylor’s research lies in the realm of Computational Biology and Bioinformatics, specifically related to applications of high throughput sequencing. This research is highly collaborative in nature involving the development of algorithms for analysis and visualization of sequencing data. The human microbiome is a specific application of interest and my lab has been involved with studies of the vaginal, gut, oral, and lung microbiomes. 

My group develops algorithms and tools for analysis and visualization of microbial communities in the context of the human microbiome. This analysis utilizes high-throughput sequencing to assay the composition of the bacteria living within and upon a host organism. Changes in this population have implications in general human health and disease and the analysis of this diverse microbiota presents unique computational challenges.


Dr. Taylor's research interests currently focus on understanding of dynamic changes in the vaginal microbiota associated with various STIs including BV, Chlamydia and HIV.  He is currently a multi-PI on an R01 and R21 grant from NIAID, and a co-investigator on two R01s, an R21, an UL1, and a P20.  In addition he serves as the contact PI for a recently awarded NSF grant that was utilized to acquire and establish a high-performance computing cluster called Tigerfish for computational biology and bioinformatics research.  Further information on this new institutional research resource is available here: https://www.lsuhsc.edu/admin/it/hpc/default.aspx


Software Tool Development

Members of our lab develop a variety of software tools to facilitate our research.  In the past we have developed systems for microbial community analysis and contributed to development of tools for metagenomic predictions.  The latest tool has been developed by John Lammons to faciliate usage of the VALENCIA classifier with Phyloseq in the R environment in order to perform community state type classifications of vaginal samples.  More information and download of the tool are available here:  https://github.com/JLammons14/ValenciaInR


Teaching Activities

Former Students

Vincent Maffei - MD/PhD, April 2, 2019: Biological Aging: The Role of the Gut Microbiota, HIV, and Alcohol Use Disorder
Clinical Rotations in Baton Rouge, LA

Guorong Xu - PhD, June 18, 2012: RNA CoMPASS: RNA Comprehensive Multi-Processor Analysis System for Sequencing
Senior Bioinformatics Engineer at University of California San Diego in San Diego, CA

A. Murat Eren - PhD, April 6, 2011: Assessing Microbial Diversity Through Nucleotide Variation
Assistant Professor in the Department of Medicine at the University of Chicago in Chicago, IL

Joseph Coco - MS, April 11, 2011: PARSES: A Pipeline for Analysis of RNA-Sequencing Exogenous Sequences
Health Systems Analyst Programmer at Vanderbilt University in Nashville, TN

Jonathan Brown - BS, May 18, 2012
Informatics Specialist for a biotech company called Counsyl in San Francisco, CA

Eugene Blanchard IV - BS, May 17, 2013
DevOps Engineer for Bus Patrol in Salt Lake City, UT


Committees & Administrative Responsibilities

Search Committee for Department Head of Genetics, 2013-2014

School of Medicine Research Advisory Committee, 2013-Present

School of Medicine International Travel Committee, 2014-Present

Basic Science Delegate to Faculty Assembly, 2015-Present

Basic Science Delegate for Administrative Coucil, 2016-2017

Microbiology, Immunology, & Parasitology Graduate Student Admissions Committee, 2016-Present

President of School of Medicine Faculty Assembly, 2018-2019

Representative to Faculty Senate, 2018-Present


Selected Publications

In The News

In January 2015, Dr. Taylor was selected as the winner of $5,000 of Illumina sequencing reagents in Illumina's MiSeq My Focus contest.  As a part of the Microbial Genomics Resource Group, the lab uses the Illumina MiSeq to explore microbial diversity in the gastrointestinal tract, urogenital tract, airways, and hospital environments.  Differences in bacterial community structure in these environments often correlate with diseases and we aim to advance diagnosis and treatment of a variety of conditions including sexually transmitted infections, obesity, diabetes and cancer.