Abstract SummaryTranscription factors (TFs) are proteins that directly interpret the genome to regulate gene expression and determine cellular phenotypes. TF identification is a common first step in unraveling gene regulatory networks. We present CREPE, an R Shiny app to catalogue and annotate TFs. CREPE was benchmarked against curated human TF datasets. Next, we use CREPE to explore the TF repertoires of Heliconius erato and Heliconius melpomene butterflies. Availability and implementationCREPE is available as a Shiny app package available at GitHub (github.com/dirostri/CREPE). Supplementary informationSupplementary data are available at Bioinformatics Advances online.
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pystablemotifs: Python library for attractor identification and control in Boolean networks
Abstract Summarypystablemotifs is a Python 3 library for analyzing Boolean networks. Its non-heuristic and exhaustive attractor identification algorithm was previously presented in Rozum et al. (2021). Here, we illustrate its performance improvements over similar methods and discuss how it uses outputs of the attractor identification process to drive a system to one of its attractors from any initial state. We implement six attractor control algorithms, five of which are new in this work. By design, these algorithms can return different control strategies, allowing for synergistic use. We also give a brief overview of the other tools implemented in pystablemotifs. Availability and implementationThe source code is on GitHub at https://github.com/jcrozum/pystablemotifs/. Supplementary informationSupplementary data are available at Bioinformatics online.
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- Award ID(s):
- 1715826
- PAR ID:
- 10362648
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Bioinformatics
- Volume:
- 38
- Issue:
- 5
- ISSN:
- 1367-4803
- Format(s):
- Medium: X Size: p. 1465-1466
- Size(s):
- p. 1465-1466
- Sponsoring Org:
- National Science Foundation
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