- 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)
- Hits: 71
- Visitors: 72
- Downloads: 6
Collections
Machanick, Philip (Assoc Prof)
RU Research Unit in Bioinformatics (RUBi)
RU Department of Computer Science
SDG 09. Industry, Innovation and Infrastructure
RU Department of Biochemistry, Microbiology and Bioinformatics
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details | SOURCE1 | Challenges with modelling transcription factor binding.pdf | 628 KB | Adobe Acrobat PDF | View Details |