Autoimmune Diseases; Computing Methodologies; Immune System Diseases; Information Science; Pattern Recognition, Automated; Virus Diseases; Computational Biology; Autoimmune Diseases of the Nervous System; Immune System Phenomena; Mathematical Concepts; Patient-Specific Modeling
Public Health Interests
Bioinformatics; Genomics; Infectious Disease; Influenza; Viruses; West Nile Virus
My research seeks to make fundamental contributions to immunology through the development and application of innovative computational methods. Somatic hypermutation (SHM) and B cell affinity maturation, the core of adaptive immunity, have been a long-term focus of my work, with a major emphasis on B cell immunoglobulin repertoire analysis. Over the past several years, my research has expanded to include methods for other high-throughput immune profiling data types, with several applications to influenza infection and vaccination responses. My lab has significant expertise in both bioinformatics and immunology and, although we do not directly perform wet-lab experiments, we work closely with experimental and clinical groups for the initial phases of hypothesis generation and experimental design.
Extensive Research Description
Information on projects is available from our lab website: http://clip.med.yale.edu
Automated analysis of high-throughput B cell sequencing data reveals a high frequency of novel immunoglobulin V gene segment alleles
Gadala-Maria D, Yaari G, Uduman M, Kleinstein SH. Automated analysis of high-throughput B cell sequencing data reveals a high frequency of novel immunoglobulin V gene segment alleles. Proceedings of the National Academies of Sciences. 2015. Feb 24;112(8):E862-70. doi: 10.1073/pnas.1417683112.
B cells populating the multiple sclerosis brain mature in the draining cervical lymph nodes
Stern JNH*, Yaari G*, Vander Heiden JA*, Church G, Donahue WF, Hintzen RQ, Huttner AJ, Laman JD, Nagra RM, Nylander A, Pitt D, Ramanan S, Siddiqui BA, Vigneault F, Kleinstein SH**, Hafler DA** and O’Connor KC**. B cells populating the multiple sclerosis brain mature in the draining cervical lymph nodes. Science Translational Medicine. 2014. Aug 6;6(248):248ra107. doi:10.1126/scitranslmed.3008879.
pRESTO: a toolkit for processing high-throughput sequencing raw reads of lymphocyte receptor repertoires
Vander Heiden JA*, Yaari G*, Uduman M, Stern JNH, O’Connor KC, Hafler DA, Vigneault F and Kleinstein SH. Bioinformatics. 2014. Jul 1;30(13):1930-2. d
Change-O: a toolkit for analyzing large-scale B cell immunoglobulin repertoire sequencing data
Gupta NT*, Vander Heiden JA*, Uduman M, Daniel Gadala-Maria, Yaari G and Kleinstein SH. Bioinformatics. 2015. Jun 10. pii: btv359.
Dynamic expression profiling of type I and type III interferon-stimulated hepatocytes reveals a stable hierarchy of gene expression
Bolen CR*, Ding S*, Robek MD**, Kleinstein SH**. Hepatology. 2013. Aug 8. doi:10.1002/hep.26657. PMID: 23929627.
Quantitative Set Analysis for Gene Expression: A method to quantify gene set differential expression including gene-gene correlations
Yaari G*, Bolen CR*, Thakar J and Kleinstein SH. Nucleic Acids Research. 2013. doi: 10.1093/nar/gkt660. PMID: 23921631.
Quantifying selection in high-throughput Immunoglobulin sequencing datasets
Yaari G, Uduman M and Kleinstein SH. Nucleic Acids Research. 2012. doi:10.1093/nar/gks457