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The Parker laboratory uses an integrative research approach in the general fields of computational biology and functional genomics. The major goal of the lab is to generate mechanistic knowledge about how disease susceptibility is encoded in the non-coding portion of the genome, with a focus on type 2 diabetes. We accomplish this through an interdisciplinary combination of molecular/cellular and computational approaches. Specifically, we generate multiple high-throughput data sets on the genome, epigenome, transcriptome, and proteome across species and in disease-relevant tissues/cells and use computational approaches to integrate and analyze this data. Looking forward, our belief is that these high-throughput biological profiling and analysis approaches will be closely tied to disease diagnosis, prognosis, and treatment—and will therefore have a tremendous influence on medicine.
研究兴趣
论文共 101 篇作者统计合作学者相似作者
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Gemma L. Pearson,Emily M. Walker,Nathan Lawlor,Anne Lietzke,Vaibhav Sidarala,Jie Zhu,Tracy Stromer,Emma C. Reck,Ava M. Stendahl, Jin Li, Elena Levi-D’Ancona, Mabelle B. Pasmooij,
biorxiv(2024)
Yasminka A Jakubek, Xiaolong Ma,Adrienne M Stilp,Fulong Yu, Jason Bacon,Justin W Wong,Francois Aguet,Kristin Ardlie,Donna Arnett, Kathleen Barnes,Joshua C Bis,Tom Blackwell,
medRxiv : the preprint server for health sciences (2024)
Arushi Varshney,Nandini Manickam,Peter Orchard,Adelaide Tovar,Zhenhao Zhang,Fan Feng,Michael R Erdos,Narisu Narisu, Christa Ventresca, Kirsten Nishino,Vivek Rai,Heather M Stringham,
bioRxiv : the preprint server for biology (2023)
American journal of human geneticsno. 2 (2023): 284-299
Alan P. Tenney,Silvio Alessandro Di Gioia,Bryn D. Webb,Wai-Man Chan,Elke de Boer, Sarah J. Garnai,Brenda J. Barry, Tammy Ray,Michael Kosicki,Caroline D. Robson,Zhongyang Zhang, Thomas E. Collins,
Nature Geneticsno. 7 (2023): 1149-1163
John T. Walker,Diane C. Saunders,Vivek Rai,Hung-Hsin Chen,Peter Orchard,Chunhua Dai,Yasminye D. Pettway, Alexander L. Hopkirk, Conrad V. Reihsmann, Yicheng Tao,Simin Fan,Shristi Shrestha,
Natureno. 7992 (2023): 621-629
Research square (2023)
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bioRxiv : the preprint server for biology (2023)
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