Article
Biochemistry & Molecular Biology
Matthew Dyer, Quy Xiao Xuan Lin, Sofiia Shapoval, Denis Thieffry, Touati Benoukraf
Summary: MethMotif is a publicly available database that provides a comprehensive repository of transcription factor-binding profiles with DNA methylation patterns. The latest release includes over 700 position weight matrices, segregated based on their cofactors and DNA methylation status. The database also offers precomputed GO annotations for human TFs and TF-co-TF complexes, allowing for a comprehensive analysis of TF functions in their context with cofactors. Furthermore, MethMotif has been expanded to include data for two additional species, increasing its applicability and value to the scientific community.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemical Research Methods
Dania Machlab, Lukas Burger, Charlotte Soneson, Filippo M. Rijli, Dirk Schuebeler, Michael B. Stadler
Summary: Proteins binding to specific nucleotide sequences, such as transcription factors, have significant roles in regulating gene expression. The monaLisa package, an R/Bioconductor package, provides methods to identify relevant transcription factors from experimental data. It allows seamless motif analyses without relying on software outside of R.
Article
Multidisciplinary Sciences
Jordan Cheng, Marco Morselli, Wei-Lun Huang, You Jeong Heo, Thalyta Pinheiro-Ferreira, Feng Li, Fang Wei, David Chia, Yong Kim, Hua-Jun He, Kenneth D. Cole, Wu-Chou Su, Matteo Pellegrini, David T. W. Wong
Summary: This study introduces uscfDNA-seq, a single-stranded cell-free DNA sequencing pipeline that reveals a population of ultrashort single-stranded cell-free DNA in human plasma. The ultrashort cell-free DNA is primarily single-stranded and is distributed evenly across chromosomes, with a similar distribution profile over functional elements as the genome, suggesting a possible terminal state of genome degradation.
Article
Biochemistry & Molecular Biology
Tom Aharon Hait, Ran Elkon, Ron Shamir
Summary: In this study, we introduce the CT-FOCS method, which uses linear mixed effect models to infer enhancer-promoter links that are specifically active in certain cell types. The results show that CT-FOCS accurately predicts these links compared to other methods, and it reveals that strictly cell type-specific EP links are rare in the human genome.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Biochemistry & Molecular Biology
Kwang-Eun Choi, Anand Balupuri, Nam Sook Kang
Summary: Several diverse proteins share similar binding sites, and comparing these binding sites can provide important insights for drug discovery and development. Understanding the water molecules surrounding the protein surface can enhance our knowledge of binding site characteristics. A novel method called TWN-RENCOD based on analyzing the aqueous environment in binding sites of similar proteins shows promising results in correlation with the activity of a known drug.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Article
Computer Science, Artificial Intelligence
Shushan Toneyan, Ziqi Tang, Peter K. Koo
Summary: This study introduces a unified evaluation framework and uses it to compare different binary and quantitative models for predicting chromatin accessibility data. The results show that quantitative modeling improves the generalizability and interpretability of the models, and a robustness metric is introduced to enhance model selection and variant effect predictions.
NATURE MACHINE INTELLIGENCE
(2022)
Article
Microbiology
Inna A. Suvorova, Mikhail S. Gelfand
Summary: Comparative genomics techniques were used to identify binding motifs of IclR-family TFs, reconstruct regulons, and analyze their content. Two main types of IclR-family motifs were described, with possible alternative modes of dimerization, as well as trends in site positioning and protein-DNA contacts. The majority of predicted protein-DNA contacts were similar for both types of motifs and aligned well with available experimental data and general protein-DNA interaction trends.
FRONTIERS IN MICROBIOLOGY
(2021)
Article
Plant Sciences
Huiling Cheng, Lifen Liu, Yuying Zhou, Kaixuan Deng, Yuanxin Ge, Xuehai Hu
Summary: An emerging approach using promoter tiling deletion via genome editing is becoming popular in plants. However, the precise positions of core motifs within plant gene promoters are largely unknown. In this study, the researchers developed TSPTFBS 2.0, which integrates DenseNet-based models and three interpretability methods to identify potential core motifs in genomic regions. The developed web-server has great potentials for providing reliable editing targets in genetic screen experiments in plants.
FRONTIERS IN PLANT SCIENCE
(2023)
Article
Multidisciplinary Sciences
Daniel Marri, David Filipovic, Omar Kana, Shelley Tischkau, Sudin Bhattacharya
Summary: The Brain and Muscle ARNTL-Like 1 protein (BMAL1) forms heterodimers with CLOCK or NPAS2 to regulate circadian clock genes. Using machine learning models, we identified features that predict BMAL1-DNA binding and provided insights into tissue specificity. We found that histone modifications, DNA shape, and the flanking sequence of E-box motifs are sufficient predictive features for BMAL1-DNA binding.
SCIENTIFIC REPORTS
(2023)
Article
Biochemical Research Methods
Jiecong Lin, Lei Huang, Xingjian Chen, Shixiong Zhang, Ka-Chun Wong
Summary: Researchers have proposed a deep learning-based tool, DeepMotifSyn, for synthesizing heterodimeric transcription factor motifs, which outperforms current predictors and has the ability to synthesize multiple motifs with different settings.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Plant Sciences
Tianming Jiao, Yipeng Huang, Ying-Ling Wu, Ting Jiang, Tongtong Li, Yanzhuo Liu, Yvchen Liu, Yunyun Han, Yajun Liu, Xiaolan Jiang, Liping Gao, Tao Xia
Summary: The tea plant contains rich polyphenolic compounds, particularly flavan-3-ols and proanthocyanidins (PAs), which are important for the flavor and disease-resistance property of tea leaves. This study focuses on the role of subgroup 5 R2R3-MYB transcription factors in the biosynthesis of PAs in tea plants. The CsMYB5s genes in tea plants respond differently to biotic and abiotic stresses, and can promote the gene expression of CsLAR and CsANR. The study also identifies key amino acids and functional domains responsible for the regulation of PA biosynthesis.
HORTICULTURE RESEARCH
(2023)
Article
Chemistry, Multidisciplinary
Shengxi Chen, Xun Ji, Larisa M. Dedkova, Sidney M. Hecht
Summary: The NF-kappa B family of transcriptional activators is responsible for the expression of key genes controlling cell development and survival. The study found that site-specific phosphorylation of the p50 subunit can significantly increase CD40 expression, providing a potential target for cancer or viral immunotherapy.
CHEMICAL COMMUNICATIONS
(2021)
Article
Biochemical Research Methods
Qianmu Yuan, Sheng Chen, Yu Wang, Huiying Zhao, Yuedong Yang
Summary: LMetalSite is an alignment-free sequence-based predictor for metal ion-binding sites. It leverages pretrained language models and transformers to improve prediction accuracy, and adopts multi-task learning to compensate for the scarcity of training data and capture the intrinsic similarities between different metal ions.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Immunology
William T. Ralvenius, Alison E. Mungenast, Hannah Woolf, Margaret M. Huston, Tyler Z. Gillingham, Stephen K. Godin, Jay Penney, Hugh P. Cam, Fan Gao, Celia G. Fernandez, Barbara Czako, Yaima Lightfoot, William J. Ray, Adrian Beckmann, Alison M. Goate, Edoardo Marcora, Carmen Romero-Molina, Pinar Ayata, Anne Schaefer, Elizabeta Gjoneska, Li-Huei Tsai
Summary: This study uncovers a novel class of anti-inflammatory molecules, represented by A11, which ameliorate neuroinflammation, pathology, and cognitive function in neurodegenerative disorders.
JOURNAL OF EXPERIMENTAL MEDICINE
(2023)
Article
Biochemical Research Methods
Chen Chen, Jie Hou, Xiaowen Shi, Hua Yang, James A. Birchler, Jianlin Cheng
Summary: DeepGRN, utilizing a combination of single attention module and pairwise attention module, can accurately predict transcription factor binding sites and outperforms other methods in the ENCODE-DREAM challenge dataset. The attention weights learned by the model are correlated with informative inputs, providing possible explanations for the predictive improvements in DeepGRN.
BMC BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Maureen Stolzer, Katherine Siewert, Han Lai, Minli Xu, Dannie Durand
BMC BIOINFORMATICS
(2015)
Article
Biochemistry & Molecular Biology
Minli Xu, Jeffrey G. Lawrence, Dannie Durand
NUCLEIC ACIDS RESEARCH
(2018)
Article
Biochemical Research Methods
Maureen Stolzer, Han Lai, Minli Xu, Deepa Sathaye, Benjamin Vernot, Dannie Durand
Article
Biochemical Research Methods
Ka Hou Chu, Minli Xu, Chi Pang Li
BMC BIOINFORMATICS
(2009)
Article
Biotechnology & Applied Microbiology
Minli Xu, Zhengchang Su
Article
Biotechnology & Applied Microbiology
Shan Li, Minli Xu, Zhengchang Su
Article
Biochemistry & Molecular Biology
Shaoqiang Zhang, Minli Xu, Shan Li, Zhengchang Su
NUCLEIC ACIDS RESEARCH
(2009)
Article
Biochemistry & Molecular Biology
James M. Mottonen, Minli Xu, Donald J. Jacobs, Dennis R. Livesay
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
(2009)