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A workflow for the computational identification of candidate regulatory elements in noncoding DNA

Published: 20 September 2014 Publication History

Abstract

Computational methods of inferring regions of noncoding DNA that regulate gene activity are important to efficient biological validation of gene regulatory control. In many cases the available resources may allow for relatively few biological assays to be performed, and computational results allow these assays to be tightly focused on the highest confidence candidate regulatory regions. Here, we present a workflow for the computational identification of candidate regulatory regions that incorporates multiple lines of evidence and illustrate its use to select high-confidence targets for experimental verification using the ciliary gene Tektin3 as an example. The Tektin3 protein is vital for ciliogenesis, a process in which cilia are formed. Cilia are important organelles of cells that are involved in numerous activities, and are related to many human diseases. The study of ciliogenesis genes may lead to advances in treatment for related diseases in humans, including diseases caused by malformation of the cilia.

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  • (2019)Visual Life Sciences Workflow Design using Distributed and Heterogeneous ResourcesIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2018.2886185(1-1)Online publication date: 2019

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  1. A workflow for the computational identification of candidate regulatory elements in noncoding DNA

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      cover image ACM Conferences
      BCB '14: Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics
      September 2014
      851 pages
      ISBN:9781450328944
      DOI:10.1145/2649387
      • General Chairs:
      • Pierre Baldi,
      • Wei Wang
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      New York, NY, United States

      Publication History

      Published: 20 September 2014

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      Author Tags

      1. bioinformatics
      2. gene regulation
      3. genetic algorithms

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      BCB '14
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      BCB '14: ACM-BCB '14
      September 20 - 23, 2014
      California, Newport Beach

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      Overall Acceptance Rate 254 of 885 submissions, 29%

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      • (2019)Visual Life Sciences Workflow Design using Distributed and Heterogeneous ResourcesIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2018.2886185(1-1)Online publication date: 2019

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