Bioinformatics and Systems Biology

The Bioinformatics and Systems Biology shared resource offers computational tools, expertise, and services for analysis of single cell and other high-throughput omics data at Winship Cancer Institute of Emory University.

The Bioinformatics and Systems Biology shared resource provides expertise and infrastructure in designing, analyses and simulation of high-throughput omics data to answer underlying biological questions. The overarching goal of our shared resource is toward development of next-generation bioinformatics platforms for supporting data driven research and discoveries at Winship.

The mission of the Bioinformatics and Systems Biology shared resource (BiSB) is to provide support for design and analysis of many next generation sequencing assays. We also offer cutting edge analysis of single cell genomics, proteomics and immune repertoire data. Among services, we provide comprehensive secondary and tertiary analysis, reporting, visualization, and results interpretation for high throughput omics data. We offer a range of downstream analyses such as mRNA expression quantification and differential analysis, isoform discovery, fusion detection, RNA editing, variant/allele analysis, methylation, genotyping, and protein-nucleic acid interaction. We place special emphasis on the continuous development of systems biology-based approaches for integrative analysis of genomics, epigenomics, proteomic, metabolomic, imaging and clinical data. Several of our best practice pipelines are accessible online for Winship researchers for routine and exploratory data analysis. Our goal is to get you the right analysis through our best practices and data-driven workflows.

Capabilities and Services

We offer bioinformatics analysis of data types from various platforms.

  • Analysis of single cell and nuclei profiling data
  • Analysis of CyTOF and multi-dimensional single cell profiling data
  • Genomics data analysis including whole genome (WGSeq), whole exome(WESeq), RNA-Seq, miRNA-Seq, whole genome bisulphite (WGBS-Seq), targeted deep sequencing (gene panels), chromatin immunoprecipitation (ChIP-Seq), transposase accessible chromatin sequencing (ATAC-Seq); and Microarrays, SNP genotyping, methylation, nanostring assays.
  • Proteomics, microbiome, and metabolomics data analysis.
  • High throughput immune repertoire analysis
  • Integrated multi-omics systems biology analysis
  • Pathway and functional network analysis (including IPA).
  • Complex analysis (diagnostic and prognostic biomarker prediction, T & B cell epitope prediction).
  • Data mining of public cancer genomics databases for validation
  • Development of analytical approaches for novel omics data types.
  • Consultation on experimental design, quality control, and post-sequencing questions.
  • Development of predictors using Bayesian, Support Vector Machine (SVM), Artificial Neural Networks (ANN) and K-Nearest Neighbor (KNN) algorithms for diagnosis and prognosis of disease
  • Prediction of immunotherapy candidates

Software and Applications

We offer bioinformatics application tools developed for cancer research and intended to equip investigators with tools to enable efficient data mining for formulating a specific research question to then engage resources and others on how best to address it.

Service Request

For assistance with our services, please fill out our request form on the PPMS service request system. View instructions for requesting a new account and for requesting/starting new project.

Contact Us

Contact Bioinformatics and Systems Biology shared resource via email at

Publication Acknowledgement Policy

The National Cancer Institute requires that publications acknowledge the Winship Cancer Institute Cancer Center Support Grant (CCSG), and it is tracking compliance. If a Winship Cancer Institute CCSG-supported Shared Resource provided data, designed the study, performed analyses, provided results used in your publication, and/or provided any systems or services that were used for the work that resulted in your publication, please include the following statement in the acknowledgment section of your publication(s):

Research reported in this publication was supported in part by the Biostatistics and Systems Biology shared resource of Winship Cancer Institute of Emory University and NIH/NCI under award number P30CA138292. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Photo of  Manoj Bhasin, PhD, MS
Manoj Bhasin, PhD, MS

Manoj Bhasin, PhD, MS

Scientific Director, Bioinformatics and Systems Biology Shared Resource
Winship Cancer Institute of Emory University

Dr. Bhasin is performing a large scale analysis of cancer gene-expression data to determine the true biological differences in different cancers, predicting biomarkers and developing cancer prediction models.

Photo of  Bhakti Dwivedi, PhD, MS
Bhakti Dwivedi, PhD, MS

Bhakti Dwivedi, PhD, MS

Associate Bioinformatics Scientist, Bioinformatics and Systems Biology Shared Resource
Winship Cancer Institute of Emory University

Dr. Dwivedi's quantitative areas of expertise include bioinformatics study/data analysis plan, bioinformatics software tool development, pathways/network analysis, phylogenetic analysis, metagenomics, cancer microbiome analysis, and external data validation.

Photo of  Khanjan "Kuki" Gandhi, MS, MBA
Khanjan "Kuki" Gandhi, MS, MBA

Khanjan "Kuki" Gandhi, MS, MBA

Senior Bioinformatics Analyst, Bioinformatics and Systems Biology Shared Resource
Winship Cancer Institute of Emory University

Ms. Gandhi provides bioinformatics support in study design, data analysis, interpretation and assessment of clinical relevance of several biological data types including next generation sequencing (NGS) data.

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