Ivan Iossifov
Associate Professor
Ph.D., Columbia University, 2008
iossifov@cshl.edu | (516) 367-6947
Every gene has a job to do, but genes rarely act alone. Biologists have built models of molecular interaction networks that represent the complex relationships between thousands of different genes. I am using computational approaches to help define these relationships, work that is helping us to understand the causes of common diseases including autism, bipolar disorder, and cancer.
Ivan Iossifov focuses on the development of new methods and tools for genomic sequence analysis and for building and using molecular networks, and he applies them to specific biomedical problems. He studies the genetics of common diseases in humans using two main tools: next-generation sequencing and molecular networks representing functional relationships among genetic loci. These approaches in combination enable the kind of large-scale studies necessary for furthering our understanding of the complex etiology of disorders such as autism, bipolar disorder, and cancer.
Portrait of a Neuroscience Powerhouse
April 27, 2018
A relatively small neuroscience group at CSHL is having an outsized impact on a dynamic and highly competitive field
Autism genetics study calls attention to impaired motor skills, general cognitive impairment
February 7, 2018
New research on the genetic causes of autism calls attention to diminished motor skills and suggests the importance of broad cognitive impairment
Why is autism more common in boys?
April 29, 2016
Ivan Iossifov talks about some of the reasons why autism disproportionately effects boys on a genetic level.
What do autism “risk genes” do?
April 21, 2016
A discussion with Ivan Iossifov with what exactly the term "risk genes" means and what they do.
How many autism “risk genes” have scientists found?
April 14, 2016
A look at the research which points to the different genes potentially at the root of autism.
Where does autism come from when it doesn’t run in the family?
April 7, 2016
Associate Professor Ivan Iossifov discusses how parents who are not autistic can pass autism onto their children through their genes.
Genetic analysis supports prediction that spontaneous rare mutations cause half of autism
September 22, 2015
Scientists find evidence suggesting that devastating “ultra-rare” mutations play a causal role in roughly half of all autism spectrum disorders.
New study casts sharpest light yet on genetic mysteries of autism
October 29, 2014
Our picture of how genetic errors contribute to autism has just gotten sharper.
A shift in the code: New method reveals hidden genetic landscape
August 18, 2014
Scientists develop algorithm to uncover genomic insertions and deletions involved in autism, OCD
CSHL receives $50 million to establish Simons Center for Quantitative Biology
July 7, 2014
CSHL announced a $50 million gift from Jim and Marilyn Simons to establish the Simons Center for Quantitative Biology.
Rodriguez-Esteban, R. and Iossifov, I. (2009) Figure mining for biomedical research. Bioinformatics, 25(16) pp. 2082-2084.
Liu, J. and Ghanim, M. and Xue, L. and Brown, C. D. and Iossifov, I. and Angeletti, C. and Hua, S. and Negre, N. and Ludwig, M. and Stricker, T. and Al-Ahmadie, H. A. and Tretiakova, M. and Camp, R. L. and Perera-Alberto, M. and Rimm, D. L. and Xu, T. and Rzhetsky, A. and White, K. P. (2009) Analysis of Drosophila segmentation network identifies a JNK pathway factor overexpressed in kidney cancer. Science, 323(5918) pp. 1218-22.
Iossifov, I. and Zheng, T. and Baron, M. and Gilliam, T. C. and Rzhetsky, A. (2008) Genetic-linkage mapping of complex hereditary disorders to a whole-genome molecular-interaction network. Genome Res, 18(7) pp. 1150-62.
Cokol, M. and Iossifov, I. and Rodriguez-Esteban, R. and Rzhetsky, A. (2007) How many scientific papers should be retracted?. EMBO Rep, 8(5) pp. 422-3.
Rodriguez-Esteban, R. and Iossifov, I. and Rzhetsky, A. (2006) Imitating manual curation of text-mined facts in biomedicine. PLoS Comput Biol, 2(9) pp. e118.
Additional materials of the author atCSHL Institutional Repository