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 …

Decoding enhancer complexity with machine learning and high-throughput discovery

GD Smith, WH Ching, P Cornejo-Páramo, ES Wong - Genome biology, 2023 - Springer
Enhancers are genomic DNA elements controlling spatiotemporal gene expression. Their
flexible organization and functional redundancies make deciphering their sequence-function …

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 …

Deep flanking sequence engineering for efficient promoter design using DeepSEED

P Zhang, H Wang, H Xu, L Wei, L Liu, Z Hu… - Nature …, 2023 - nature.com
Designing promoters with desirable properties is essential in synthetic biology. Human
experts are skilled at identifying strong explicit patterns in small samples, while deep …

Revealing enzyme functional architecture via high-throughput microfluidic enzyme kinetics

CJ Markin, DA Mokhtari, F Sunden, MJ Appel, E Akiva… - Science, 2021 - science.org
INTRODUCTION Enzymes possess extraordinary catalytic proficiency and specificity. These
properties ultimately derive from interactions not just between the active-site residues and …

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 …

Evaluating deep learning for predicting epigenomic profiles

S Toneyan, Z Tang, PK Koo - Nature machine intelligence, 2022 - nature.com
Deep learning has been successful at predicting epigenomic profiles from DNA sequences.
Most approaches frame this task as a binary classification relying on peak callers to define …

Rational design of minimal synthetic promoters for plants

YM Cai, K Kallam, H Tidd, G Gendarini… - Nucleic Acids …, 2020 - academic.oup.com
Promoters serve a critical role in establishing baseline transcriptional capacity through the
recruitment of proteins, including transcription factors. Previously, a paucity of data for cis …

Decoding non-coding variants: recent approaches to studying their role in gene regulation and human diseases

EG Peña-Martínez… - Frontiers in bioscience …, 2024 - pmc.ncbi.nlm.nih.gov
Genome-wide association studies (GWAS) have mapped over 90% of disease-and
quantitative-trait-associated variants within the non-coding genome. Non-coding regulatory …

Global importance analysis: An interpretability method to quantify importance of genomic features in deep neural networks

PK Koo, A Majdandzic, M Ploenzke… - PLoS computational …, 2021 - journals.plos.org
Deep neural networks have demonstrated improved performance at predicting the
sequence specificities of DNA-and RNA-binding proteins compared to previous methods …