The Computational Biology group at the New York Genome Center (NYGC) is a team of scientists, analysts and programmers who conduct research in cancer genomics, transcriptomics, genetics of Mendelian and complex diseases, statistical genetics, metagenomics, epigenomics, and genome and transcriptome assembly. This work includes the development of tools and analysis pipelines. The Computational Biology Group […]
Yaniv Erlich’s lab focuses on developing new strategies at the New York Genome Center in order to harness datasets from millions of people through social media and scientific resources. With that information, the lab will work to dissect the genetic architecture of complex traits to work toward bridging the missing heritability gap. Erlich’s lab consists […]
The Imielinski lab applies cancer genome assembly to study long range DNA structure in tumors. A key goal of the lab is to understand how complex somatic DNA rearrangements shape the tumor epigenome and drive cancer progression. More fundamentally, the lab is interested in using structural variation as a lens to study genomic plasticity and […]
The Landau Lab develops computational and experimental tools to study cancer evolution. Our research is geared towards uncovering basic principles in evolutionary biology, using both patient derived samples and experimental systems for modeling cancer evolution. In addition, we seek to apply this knowledge to designing the next generation of precision medicine tools to overcome cancer evolution, as a […]
Neville Sanjana’s lab develops technologies to understand how human genetic variants cause diseases of the nervous system and cancer. The lab employs a multi-disciplinary approach, combining genome engineering, pooled genetic screens, bioinformatics, electrophysiology, and imaging, to dissect the inner workings of the human genome and its dysfunction in autism and tumor evolution. The Sanjana lab […]
Dr. Wigler’s research is presently focused on the genomics of cancer and the genetics of autism and related disorders. Together with members of his laboratory they have demonstrated the feasibility of single cell sequencing for genomic analysis and expects this work will eventually improve the targeting of cancer treatments and lead to early and less […]
Dr. Darnell studies RNA biology and next-generation human genomics, work that arose from his clinical and basic studies of patients with paraneoplastic neurologic disorders (PNDs). PNDs are a group of rare brain diseases thought to arise when tumors – typically breast, ovarian, or lung cancers – start making proteins that are normally only made by […]
Tuuli Lappalainen’s lab studies functional genetic variation in human populations. It is particularly interested in regulatory variation affecting the transcriptome, as well as cellular mechanisms underlying genetic associations to disease. The lab integrates computational analysis of genomic and transcriptomic data with population genetic and experimental analysis. The lab is also affiliated with the Department of […]
Joe Pickrell’s computational genomics lab develops novel statistical approaches to transform large-scale genomic data into improved understanding of human biology and evolution. Much of the Pickrell Lab’s work is focused on understanding natural human variation – the evolutionary and molecular mechanisms that lead to differences in phenotypes and disease risk between individuals.
Rahul Satija’s lab studies the causes and consequences of cellular heterogeneity in complex biological systems. His group is particularly interested in single cell genomics, with active development in both the dry and wet lab. The lab integrates novel statistical and machine learning-based methods with experimental analysis in order to better understand how cells work together […]
CONTACT: Twitter: @NYGCTech Email: firstname.lastname@example.org The Technology Innovation Lab is a dedicated incubator within the New York Genome Center (NYGC) comprised of a multidisciplinary team in which staff scientists and faculty, as well as many research collaborators, can explore and test breakthrough genomic tools and ideas. We serve as a creative hub for generating new […]
High-throughput magnetic particle washing in nanoliter droplets using serial injection and splitting.
Stephenson W.Micro and Nano Systems Letters. 2018 June 21.
Phenotypic Convergence: Distinct Transcription Factors Regulate Common Terminal Features.
Konstantinides N, Kapuralin K, Fadil C, Barboza L, Satija R, Desplan C.
Cell. 2018 June 9.
YES1 amplification is a mechanism of acquired resistance to EGFR inhibitors identified by transposon mutagenesis and clinical genomics.
Fan PD, Narzisi G, Jayaprakash AD, Venturini E, Robine N, Smibert P, Germer S, Yu HA, Jordan EJ, Paik PK, Janjigian YY, Chaft JE, Wang L, Jungbluth AA, Middha S, Spraggon L, Qiao H, Lovly CM, Kris MG, Riely GJ, Politi K, Varmus H, Ladanyi M.
Proc Natl Acad Sci U S A. 2018 June 6.
Organoid profiling identifies common responders to chemotherapy in pancreatic cancer.
Tiriac H, Belleau P, Engle DD, Plenker D, Deschênes A, Somerville T, Froeling FEM, Burkhart RA, Denroche RE, Jang GH, Miyabayashi K, Young CM, Patel H, Ma M, LaComb JF, Palmaira RLD, Javed AA, Huynh JA, Johnson M, Arora K, Robine N, Shah M, Sanghvi R, Goetz AB, Lowder CY, Martello L, Driehuis E, Lecomte N, Askan G, Iacobuzio-Donahue CA, Clevers H, Wood LD, Hruban RH, Thompson ED, Aguirre AJ, Wolpin BM, Sasson A, Kim J, Wu M, Bucobo JC, Allen PJ, Sejpal DV, Nealon W, Sullivan JD, Winter JM, Gimotty PA, Grem JL, DiMaio DJ, Buscaglia JM, Grandgenett PM, Brody JR, Hollingsworth MA, O’Kane GM, Notta F, Kim EJ, Crawford JM, Devoe CE, Ocean A, Wolfgang CL, Yu KH, Li E, Vakoc CR, Hubert B, Fischer SE, Wilson JM, Moffitt RA, Knox JJ, Krasnitz A, Gallinger S, Tuveson DA.
Cancer Discovery. 2018 May 31.
Mapping and characterizing N6-methyladenine in eukaryotic genomes using single molecule real-time sequencing.
Zhu S, Beaulaurier J, Deikus G, Wu T, Strahl M, Hao Z, Luo G, Gregory JA, Chess A, He C, Xiao A, Sebra R, Schadt EE, Fang G.
Genome Research. 2018 May 15.
Integrated design, execution, and analysis of arrayed and pooled CRISPR genome-editing experiments.
Canver MC, Haeussler M, Bauer DE, Orkin SH, Sanjana NE, Shalem O, Yuan GC, Zhang F, Concordet JP, Pinello L.
Nat Protocols. 2018 Apr. 12.
Effects of 3D culturing conditions on the transcriptomic profile of stem-cell-derived neurons.
Tekin H, Simmons S, Cummings B, Gao L, Adiconis X, Hession CC, Ghoshal A, Dionne D, Choudhury SR, Yesilyurt V, Sanjana NE, Shi X, Lu C, Heidenreich, Pan JQ, Levin JZ & Zhang F.
Nature Biomedical Engineering. 2018 Apr. 9.
Integrated analysis of single cell transcriptomic data across conditions, technologies, and species
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Nature Biotechnology. 2018 Apr. 2.
taxMaps: Comprehensive and highly accurate taxonomic classification of short-read data in reasonable time.
Corvelo A, Clarke WE, Robine N, Zody MC.
Genome Research. 2018 Mar. 27.
Lancet: genome-wide somatic variant calling using localized colored DeBruijn graphs.
Communications Biology. 2018 Mar. 22.
- High-throughput magnetic particle washing in nanoliter droplets using serial injection and splitting.