The Bioinformatics Shared Resource works closely with the other Shared Resources that generate large, complex data sets. The faculty in the Biostatistics Shared Resource provide complementary expertise and assist with the data analysis. The Resource Directors collaborate with users to design experiments, develop new methods for data analysis and interpretation, to integrate therapeutic knowledge and to assist with grant writing and data processing for publications.

Several types of innovative technologies used by researchers at the UNM Cancer Center produce large and complicated high-dimensional data that require specialized expertise, computational resources and software for analysis. These include

  • next-generation sequencing (NGS) studies,
  • high-throughput drug screening (HTS), coupled with cheminformatics, target analytics and pharmacoinformatics, and
  • super-resolution microscopy, including quantitative and hyperspectral techniques.
Bioinformatics Image

Providing access to high-quality, expert and cost-effective data analysis solutions is just as important as making cutting-edge instrumentation and lab techniques available to users, so that they can make the best use of the data that are produced.

The Bioinformatics and High-Dimensional Data Analysis Shared Resource provides UNM Cancer Center members with the expertise and technologies necessary to make use of these complicated data sets in a way that supports the goals of the UNM Cancer Center Research Programs and promotes innovative basic and translational cancer research in the UNM Cancer Center catchment area.

Use the Bioinformatics Tools

Bioinformatics Shared Resource

Yan Guo, PhD

Director, Bioinformatics Shared Resource
Office: 505-925-0099
Email Dr. Guo

Jeremy Edwards, PhD

Associate Director

Tudor Oprea, MD, PhD

Associate Director

Olufunmilola (Mary) Oyebamiji, MS

Bioinformatician, Data Analysis

Jiapeng He, MS

Bioinformatician, Data Analysis

Kathryn Brayer, PhD

Bioinformatician, Data Analysis
also supports Analytical and Translational Genomics

Cancer Research Facility (CRF): Ground Floor, Room 100A

To acknowledge use of this shared resource, please include the following in your publications:

This research was partially supported by UNM Comprehensive Cancer Center Support Grant NCI P30CA118100 and the Bioinformatics and High Dimensional Data Analysis shared resource.

Bioinformatics Goals

Provide Informatics, Analytics and Knowledge Management Support via Cost-Effective Services, Technologies, Equipment and Expertise to Support the three UNM Cancer Center Research Programs.

  • Promotes outstanding transdisciplinary research
  • Supports the discovery of genetic and other factors contributing to cancer in New Mexico

Develop Custom Bioinformatics Tools and Pipelines tailored to UNM Cancer Center research needs.

  • Promotes outstanding transdisciplinary research
  • Supports the discovery of genetic and other factors contributing to cancer in New Mexico

Provide Education and Promote Awareness about Bioinformatics Technologies and Services.

  • Promotes the education and training of a cancer workforce

Faculty and Staff

Guo ImageYan Guo, PhD

Director of the Bioinformatics and High Dimensional Data Analysis Shared Resource
Associate and Endowed Professor of Molecular Medicine

Cancer Research Facility, Room 100A
E-mail Dr. Yan Guo

Education and Training

PhD Computer Science, focsed on Bioinformatics, University of South Carolina
MS Engineering, University of South Carolina
BS Computer Science, Minor in Japanese, University of Minnesota

Research Interests

Development of bioinformatics methodology and analysis approaches for genomic and genetics studies.

Edwards ImageJeremy Edwards, PhD

Co-Director of the Bioinformatics and High Dimensional Data Analysis Shared Resource
Professor of Chemistry and Chemical Biology
Professor of Chemical and Biological Engineering
Professor of Molecular Genetics and Microbiology

Cancer Research Facility, Room 117
E-mail Dr. Edwards

Education and Training

Postdoctoral training in Genetics, Harvard Medical School
PhD Bioengineering, University of California San Diego
MS Bioengineering, University of California San Diego
BS Mechanical Engineering, University of Texas Arlington

Research Interests

Bioinformatics, genome technologies, next generation sequencing technology, systems biology, spatial regulation of signaling pathways.

Oprea ImageTudor Oprea, MD, PhD

Co-Director of the Bioinformatics and High Dimensional Data Analysis Shared Resource
Professor and Chief of the Division of Translation Informatics, Department of Internal Medicine
E-mail Dr. Oprea

Research Interests

Cheminformatics, target analytics and pharmacoinformatics, data mining and analyses, clinical drug  properties and competitive drug intelligence.

Education and Training

Postdoctoral training at Los Alamos National Laboratory in Theoretical Biology, with Angel García
Postdoctoral training at the Center for Molecular Design, Washington University, with Garland Marshall
MD, University of Medicine and Pharmacy in Timisoara, Romania
PhD, University of Medicine and Pharmacy in Timisoara, Romania

Guo Lab

Bioinformatics is a multidisciplinary field which combines concepts and skills from biology, computer science and biostatistics to solve large and complex biomedical research problems. Our lab carries out bioinformatics, genomic research in data mining, machine learning, and high throughput genomic data quality control. Our Bioinformatics Shared Resources also provides bioinformatics support for The University of New Mexico Comprehensive Cancer Center and beyond.

Yan Guo, PhD, Associate and Endowed Professor Director, Bioinformatics Shared Resource
CV | Send an email

Hui Yu, PhD, Research Fellow
CV | Send an email

Olufunmilola (Mary) Oyebamiji, Research Scientist
CV | Send an email

Jiapeng He, Research Scientist
CV | Send an email

Limin Jiang, Visiting Scholar
CV | Send an email

Resource Links

UCLA’s Statistical Consulting Group: Resources for common statistical software packages and tutorials for statistical concepts

SWOG’s Statistical Tools: Sample size and simple analysis software

Bioconductor: an open source software for bioinformatics which provides tools for the analysis and comprehension of high-throughput genomic data using the R statistical programming language.

PLINK: a free, open-source whole genome association analysis toolset focusing on analysis of genotype/phenotype data.

PLINK/SEQ: an open-source C/C++ library providing a platform for analytic tool development for variation data from large-scale resequencing and genotyping projects, particularly whole-exome and whole-genome studies.

METAL: a tool for meta-analysis of genomewide association scans by combining test statistics and standard errors or p-values across multiple studies.

MAGENTA: a computational tool that tests for enrichment of genetic associations in predefined biological processes or sets of functionally related genes.

IMPUTE2: a genotype imputation and haplotype phasing program

Software for genetic variant identification in next-generation genome sequencing studies Tools for functional annotation of genetic variants from high-throughput sequencing data A more complete list of software for analysis of next-generation sequencing data is available:

The following are freely available online resources that Bioinformatics Shared Resource maintains. They are available to all UNM Cancer Center members.