Center for Bioinformatics and Genomics

Mission: To promote bioinformatics, computational biology, and translational research of human complex diseases/traits with the goal of accelerating the pace of scientific discovery, reducing mortality and improving the quality of life.

Research: The Center will conduct multidisciplinary research with the goal of accelerating the pace of scientific discovery, reducing mortality and improving the quality of life of Americans.


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Current research areas:

  • Analytical methodology development for linkage and association studies, genome-wide association studies, next generation sequencing studies, and gene expression, epigenenic/epigenomic, and proteomic studies.
  • Clinical, genetic epidemiologic, genomic and proteomic studies of human complex diseases/traits, such as osteoporosis, sarcopenia, obesity, periodontal diseases, and female health related diseases/traits (e.g., age at menarche, age at menopause).
  • Genetic epidemiologic studies of psychological traits, such as smoking, alcohol drinking, and exercise.
  • Molecular/cellular biological studies of multiple signaling and gene regulation pathways involved in bone formation.  

Future research directions:

  • Short term goal: to establish bioinformatics, genomic and computational research as a major area of research strength at Tulane University for research funding and publications.
  • Long term goal: to build a first class center leading cutting edge research in bioinformatics, genetics, genomics, computational, molecular biological and translational research of human diseases, to attain national and international recognition for excellence in bioinformatic, genomic and computational research, and to be predominantly extramurally funded.


The Center will promote interactive and collaborative research in various fields, such as bioinformatics, biostatistics, computational biology, genetics, genomics, and proteomics.



The Center is dedicated to provide a broad range of services and education opportunities to the research community inside and outside Tulane University. Available services include:

  • To assist researchers in exploiting existing and emerging bioinformatic and computational approaches and tools.
  • To help researchers focus on their own expertise in research and be increasingly competitive in extramural grant application through assistance of bioinformatics from the Center.
  • To provide education and training opportunities to young and new investigators in bioinformatics and the related fields.
  • To provide services for various types of genomic and proteomic studies such as genome-wide SNP genotyping, protein expression profiling, and genomic methylation pattern characterization.
  • To provide aids in designing and managing biological databases, supports for exploring the high performance computing facilities housed in the Center, and appropriate statistical, genetic, and genomic analyses of experimental data, based on the Center investigators' expertise.




Postdocs and Students




Multiple postdoctoral positions are available at Department of biostatistics and bioinformatics at Tulane University. Applicants must have a Ph.D. and/or a M.D. degree. Background and prior experience in human genetics and/or bone biology is desirable.

Position 1 (molecular/cellular bone biology): The successful candidate will participate in molecular bone biology research projects aimed to identify novel mechanisms of gene regulation for bone formation.  Major responsibilities will include performing in vitro and in vivo experiments, such as cell culture, DNA manipulation, Western blot, qPCR, IHC, IF, EMSA. ChIP, genotyping and characterizing knockout and transgenic mice, and analyzing research data. Experience in advanced molecular and cellular biology and genetic mouse models is a plus. If you are interested in the position, please contact: Dr. Ming Zhao, Ph.D.,

Position 2 (statistical genetics and bioinformatics):  The successful candidate will involve in data analysis and method development for genome-wide association studies using genomic and sequence data, data modeling and analysis for epigenomic studies, and integrative analysis of genetic variation at multiple biological levels. Applicants must have background in statistical genetics, bioinformatics, or related areas. If you are interested in the position, please contact: Dr. Jian Li, Ph.D.,

Position 3 (functional genomics and proteomics): The successful candidate will participate in functional genomics and/or proteomics research projects for osteoporosis and related diseases (e.g., genome-wide gene expression analyses using microarrays and proteomics analyses using liquid chromatography and mass spectrometry, etc). If you are interested in the position, please contact: Dr. Fei-Yan Deng, Ph.D.,

Position 4 (epigenetics and epigenomics): The successful candidate will involve in developing and executing research projects related to identification and characterization of epigenetic / epigenomic factors associated with osteoporosis and related diseases. Prior experience in chromatin immunoprecipitaion (ChIP) and/or related techniques (e.g., ChIP-chip, ChIP-seq, reporter assay, etc) is necessary. If you are interested in the position, please contact: Dr. Hui Shen, Ph.D.,

Position 5 (genetic epidemiology): The successful candidate will participate in genetic epidemiological research projects for osteoporosis and related diseases (e.g., candidate gene and/or genome-wide association studies, DNA re-sequencing studies, nutrigenetic or nutrigenomic studies, etc). If you are interested in the position, please contact: Dr. Yongjun Liu, Ph.D.,




In the recent issue of ISCB (International Society of Computational Biology) newsletter, our paper on comparing de novo assembly approaches for next-generation sequencing data (Lin, 2011) has been indicated to be one of five top accessed papers published on the journal of Bioinformatics in 2011:

In this study, motivated by the need of evaluation and information for selecting appropriate de novo assembly tools for next-generation sequencing data to produce the best performance under a specific set of conditions, we studied and compared the performance of commonly used de novo assembly tools specifically designed for next-generation sequencing data, including SSAKE, VCAKE, Euler-sr, Edena, Velvet, ABySS and SOAPdenovo. Tools were compared using several performance criteria, including N50 length, sequence coverage and assembly accuracy. Various properties of read data, including single-end/paired-end, sequence GC content, depth of coverage and base calling error rates, were investigated for their effects on the performance of different assembly tools. We also compared the computation time and memory usage of these seven tools. Based on the results of our comparison, the relative performance of individual tools is summarized and tentative guidelines for optimal selection of different assembly tools, under different conditions, are provided.

The journal of Bioinformatics is the leading journal in the field of Bioinformatics with an Impact Factor of 5.468: the top ranked journal in Mathematics and Computational Biology. With a focus on new developments in genome bioinformatics and computational biology, the journal publishes reports for biologically interesting discoveries using computational methods and applications used for experiments.


Yong Lin, Jian Li, Hui Shen, Lei Zhang, Christopher J. Papasian and Hong−Wen Deng. Comparative studies of de novo assembly tools for next-generation sequencing technologies. Bioinformatics. (2011) 27(15): 2031-2037.



  • Graduate student Shaolong Cao was selected as an oral presentation of ASHG 2013. He also received a travel award from NSF support for ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics (ACM BCB), September 2013.

  • Graduate student Rongrong Zhang received "Young Investigator Travel Award" of  American Society for Bone and Mineral Research (ASBMR) 2013 Annual Meeting.
  • A graduate student, Yu Zhou, received scholarship to attend the 18th Summer Institute in Statistical Genetics (SISG 2013) and the 5th Summer Institute in Statistics and Modeling in Infectious Diseases (SISMID 2013).
  • Dr. Lei Zhang has received "2013 Health Sciences Research Days Award for Excellence in Research and Presentation" for his study on multi-stage Genome-Wide association meta-analyses.
  • Dr. Jigang Zhang is a recipient of a 2011 ASHG Trainee Research Semifinalist Award. His abstract was reviewed by the Scientific Program Committee and was selected as one of 79 out of nearly 450 trainee submissions.
  • Dr. Fei-Yan Deng has received "2011 ASBMR Young Investigator Travel Grant" for her outstanding research on "Peripheral Blood Monocyte-Expressed Anxa2 Gene Is Involved in Pathogenesis of Osteoporosis in Humans."
  • Dr. Hongbin Liu has received "2011 ASBMR Young Investigator Travel Grant" for his outstanding research on "Microtubule contribution to osteoclastogenesis, -- low bone mass phenotype of stathmin deficient mice."
  • Xiaojing Xu has received "2011 ASBMR Young Investigator Travel Grant" for her outstanding research on "DNA methylation levels of CYP2R1 and CYP24A1 predict vitamin D dose-response variation."


Publications in 2011:


Grants funded in 2011:

  • Ladies Leukemia League and Tulane Cancer Center Grant:
    Title: Bioinformatics technique for accurate subtype classification of myelodysplastic syndrome (MDS)
    PI: Dr. Yu-Ping Wang
    Funding: $50,000



Contact us:

Offices and Clinical section in Tidewater building:

1440 Canal Street, Suite 2001

New Orleans, LA 70112-2705

Tel: 504-988-1142

Fax:  504-988-1706

Offices and molecular biology lab in JBJ building:
333 Liberty Street , 3rd floor

New Orleans, LA 70112

Tel: 504-988-6987

Fax:  504-988-1706  






Department of Biostatistics, 1440 Canal Street, Suite 2001, New Orleans, LA 70112, 504-988-5164