Challenges with modelling transcription factor binding

Title: Challenges with modelling transcription factor binding
Creator: Machanick, Philip, Kibet, Caleb K
Subject: To be catalogued
Date: 2017
Type: text
Type: article
Identifier: http://hdl.handle.net/10962/439158
Identifier: vital:73551
Identifier: 10.1109/NEXTCOMP.2017.8016178
Description: Modelling transcription factor binding presents a number of challenges. In its simplest form, binding can be modelled by a consensus sequence but a number of factors including degeneracy of binding sites, alternative modes of binding and differences between artificially-constructed and in vivo DNA make modelling binding complex. In this paper we outline difficulties and report on progress with improving modelling of binding. We focus on improving measurement of binding models, a necessary prerequisite for finding better models.
Format: 6 pages, pdf
Language: English
Relation: IEEE Xplore, Machanick, P. and Kibet, C.K., 2017, July. Challenges with modelling transcription factor binding. In 2017 1st International Conference on Next Generation Computing Applications (NextComp) (pp. 68-74). IEEE, IEEE Xplore volume 2017 number 1 68 74 2017 978-1-5386-3831-6
Rights: Publisher
Rights: Use of this resource is governed by the terms and conditions of the IEEE Xplore Terms of Use Statement (https://ieeexplore.ieee.org/Xplorehelp/overview-of-ieee-xplore/terms-of-use)

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Machanick, Philip (Assoc Prof)

RU Department of Computer Science

RU Research Unit in Bioinformatics (RUBi)

RU Department of Biochemistry, Microbiology and Bioinformatics

SDG 09. Industry, Innovation and Infrastructure

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