HTS-IBIS: fast and accurate inference of binding site motifs from HT-SELEX data
Abstract
SummaryRecent technological advancements enable measuring the binding of a transcription factor to thousands of DNA sequences, in order to infer its binding preferences. High-throughput-SELEX measures protein-DNA binding by deep sequencing over several cycles of enrichment. We devised a new algorithm called HTS-IBIS for the inference task. HTS-IBIS corrects for technological biases, selects the cycle and k, and builds a motif starting from a consensus k-mer in that cycle. In large scale tests, HTS-IBIS outperformed the extant automatic algorithm for the motif finding task on both in vitro and in vivo binding prediction.\n\nAvailabilityHTS-IBIS is available on acgt.cs.tau.ac.il/HTS-IBIS.\n\nContactrshamir@tau.ac.il
02 /Specification & Classification
Click any tag to browse matching papersReproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Inferring binding specificities of human transcription factors with the wisdom of crowds
Nikita Gryzunov, Dmitry Penzar, … Ivan V. Kulakovskiy·Cell ReportsPeer-reviewed·Oct 1, 2026
- MotifMark: Finding Regulatory Motifs in DNA Sequences
Hamid Reza Hassanzadeh, Pushkar Kolhe, … May Dongmei Wang·Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)Peer-reviewed·Jul 1, 2017
- Bayesian Markov models improve the prediction of binding motifs beyond first order
Wanwan Ge, Markus Meier, … Johannes Söding·NAR Genomics and BioinformaticsPeer-reviewed·Apr 9, 2021
- A Weighted Two-stage Sequence Alignment Framework to Identify DNA Motifs from ChIP-exo Data
Yang Li, Yizhong Wang, … Bingqiang Liu·PatternsPeer-reviewed·Feb 2, 2024
- Discovering a less-is-more effect to select transcription factor binding sites informative for motif inference
Jinrui Xu, Jiahao Gao, Mark Gerstein·bioRxiv·Nov 29, 2020
- Systematic Prediction of Regulatory Motifs from Human ChIP-Sequencing Data Based on a Deep Learning Framework
Jinyu Yang, Anjun Ma, … Qin Ma·Nucleic Acids ResearchPeer-reviewed·Jul 24, 2019