Christopher M. Taylor, PhD
Department of Microbiology, Immunology & Parasitology
Bioinformatics, Biostatistics, & Computational Biology Core
Louisiana Biomedical Research Network
533 Bolivar Street, Room 605
New Orleans, LA 70112
Office: (504) 568-4065
Lab: (504) 568-2215
⇒ Curriculum Vitae §
⇒ Microbial Genomics Resource Group §
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 recently appointed as the Director of the Bioinformatics, Biostatistics and Computational Biology Core of the Louisiana Biomedical Research Network. His research laboratory maintains several terabytes of sequence data and designs innovative software systems for visualization and analysis of high-throughput sequencing experiments.
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.
Visual and statistical analysis for microbial communities (Viamics)
My group is developing algorithms and tools for analysis of microbial community sequencing data 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. The system we have developed allows for visualization and manipulation of sequencing results as well as hypothesis testing. This system is very flexible and integrates diversity analysis, rarefaction curves, relative abundance pie charts, dendrograms, dot plots, and other important measures of community differences into a graphical framework that is easy to use for biological researchers with little technical training.
RNA Comprehensive Multi-Processor Analysis System for Sequencing (RNA CoMPASS)
My group is also developing algorithms and analysis tools for RNA-Sequencing. RNA-Sequencing involves the application of high-throughput sequencing to investigate the RNA present in a given sample. This provides biologists with a way to study the impact of various factors on the transcriptome but poses a variety of computational challenges including dealing with splice junctions when mapping back to the reference genome. We have merged the functionality of the PARSES system described below with this work on RNA-Sequencing to create a Comprehensive Multi-Processor Analysis System for Sequencing which we call RNA CoMPASS. This new system provides all-in-one functionality including the typical endogenous RNA-Sequencing analysis along with the investigation of exogenous sequences pioneered in PARSES. RNA CoMPASS is deployable on either a local cluster or a grid environment managed by PBS submission to accelerate the analysis of large sequencing studies.
Pipeline for Analysis of RNA-Seq Exogenous Sequences (PARSES)
We developed PARSES to allow researchers to uncover and investigate sequences in their samples arising from organisms other than the host. This is a relatively understudied area of RNA-Sequence analysis as most researchers focus only on the sequences that map back to the host genome and discard any non-mapping reads. The PARSES system focuses instead on those reads which do not map to the host genome and performs an extensive analysis of these sequences to investigate their origin. The PARSES system was designed to provide for an easy, automated installation and updating of existing system components as necessary.
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
"Meren" 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
"Johnny" Jonathan Brown - BS, May 18, 2012
Informatics Specialist for a biotech company called Counsyl in San Francisco, CA
Counsyl provides universal genetic testing for prospective parents to council them on potential genetic diseases
|Committees & Administrative Responsibilities
Search Committee for Department Head of Genetics, 2013-2014
School of Medicine Research Advisory Committee, 2013-2015
School of Medicine International Travel Committee, 2014-2016
Basic Science Delegate to Faculty Assembly, 2015-2017
Full Publication List on Pubmed
|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. The new University Medical Center will be opening its doors this summer and we intend to use these sequencing reagents to augment a joint study of the host and environmental microbial interactions as patients populate the new intensive care units. We hope that our findings will have a positive impact on the standard of care regarding environmental precautions and particularly stemming the spread of antibiotic resistant microorganisms.