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Frank J. Manion

Researcher at University of Michigan

Publications -  35
Citations -  1613

Frank J. Manion is an academic researcher from University of Michigan. The author has contributed to research in topics: Ontology (information science) & Genome-wide association study. The author has an hindex of 16, co-authored 33 publications receiving 1407 citations. Previous affiliations of Frank J. Manion include Chonnam National University & University of Texas Health Science Center at Houston.

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A comprehensive human linkage map with centimorgan density

TL;DR: A comprehensive human linkage map is presented here, consisting of 5840 loci, of which 970 are uniquely ordered, covering 4000 centimorgans on the sex-averaged map and achieving one of the first goals of the Human Genome Project--a comprehensive, high-density genetic map.
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Genome-wide association study of colorectal cancer identifies six new susceptibility loci

Fredrick R. Schumacher, +103 more
TL;DR: Six new susceptibility loci reaching a genome-wide threshold of P<5.0E-08 are described, providing additional insight into the underlying biological mechanisms of colorectal cancer and demonstrating the scientific value of large consortia-based genetic epidemiology studies.
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Novel Common Genetic Susceptibility Loci for Colorectal Cancer

Stephanie L. Schmit, +198 more
TL;DR: This article identified 42 loci (P < 5x10−8) associated with risk of colorectal cancer (CRC) and expanded consortium efforts facilitating the discovery of these loci.
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Identification of Susceptibility Loci and Genes for Colorectal Cancer Risk

Chenjie Zeng, +107 more
- 01 Jun 2016 - 
TL;DR: In this article, the authors conducted a genome-wide association study to identify risk loci for colorectal cancer (CRC) and found that the most significant variants in each locus ranged from 3.92 −8 to 1.24 −12.
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Application of Bayesian decomposition for analysing microarray data.

TL;DR: The ability of the algorithm to provide insight into the yeast cell cycle is demonstrated, including identification of five temporal patterns tied to cell cycle phases as well as the identification of a pattern tied to an approximately 40 min cell cycle oscillator.