Transcription factor–DNA binding: beyond binding site motifs

S Inukai, KH Kock, ML Bulyk - Current opinion in genetics & development, 2017 - Elsevier
Sequence-specific transcription factors (TFs) regulate gene expression by binding to cis-
regulatory elements in promoter and enhancer DNA. While studies of TF–DNA binding have …

[HTML][HTML] The genetics of transcription factor DNA binding variation

B Deplancke, D Alpern, V Gardeux - Cell, 2016 - cell.com
Most complex trait-associated variants are located in non-coding regulatory regions of the
genome, where they have been shown to disrupt transcription factor (TF)-DNA binding …

[HTML][HTML] Controlling gene expression with deep generative design of regulatory DNA

J Zrimec, X Fu, AS Muhammad, C Skrekas… - Nature …, 2022 - nature.com
Abstract Design of de novo synthetic regulatory DNA is a promising avenue to control gene
expression in biotechnology and medicine. Using mutagenesis typically requires screening …

Short tandem repeats bind transcription factors to tune eukaryotic gene expression

CA Horton, AM Alexandari, MGB Hayes, E Marklund… - Science, 2023 - science.org
Short tandem repeats (STRs) are enriched in eukaryotic cis-regulatory elements and alter
gene expression, yet how they regulate transcription remains unknown. We found that STRs …

[HTML][HTML] Cistrome and epicistrome features shape the regulatory DNA landscape

RC O'Malley, SC Huang, L Song, MG Lewsey… - Cell, 2016 - cell.com
The cistrome is the complete set of transcription factor (TF) binding sites (cis-elements) in an
organism, while an epicistrome incorporates tissue-specific DNA chemical modifications and …

[HTML][HTML] Low-affinity binding sites and the transcription factor specificity paradox in eukaryotes

JF Kribelbauer, C Rastogi… - Annual review of cell …, 2019 - annualreviews.org
Eukaryotic transcription factors (TFs) from the same structural family tend to bind similar DNA
sequences, despite the ability of these TFs to execute distinct functions in vivo. The cell …

[HTML][HTML] Support vector machines on the D-Wave quantum annealer

D Willsch, M Willsch, H De Raedt… - Computer physics …, 2020 - Elsevier
Kernel-based support vector machines (SVMs) are supervised machine learning algorithms
for classification and regression problems. We introduce a method to train SVMs on a D …

[HTML][HTML] Quantum annealing versus classical machine learning applied to a simplified computational biology problem

RY Li, R Di Felice, R Rohs, DA Lidar - NPJ quantum information, 2018 - nature.com
Transcription factors regulate gene expression, but how these proteins recognize and
specifically bind to their DNA targets is still debated. Machine learning models are effective …

Massively parallel assays and quantitative sequence–function relationships

JB Kinney, DM McCandlish - Annual review of genomics and …, 2019 - annualreviews.org
Over the last decade, a rich variety of massively parallel assays have revolutionized our
understanding of how biological sequences encode quantitative molecular phenotypes …

[HTML][HTML] Predicting DNA structure using a deep learning method

J Li, TP Chiu, R Rohs - Nature Communications, 2024 - nature.com
Understanding the mechanisms of protein-DNA binding is critical in comprehending gene
regulation. Three-dimensional DNA structure, also described as DNA shape, plays a key …