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Biochemistry & Molecular Biology
Fuhao Zhang, Min Li, Jian Zhang, Lukasz Kurgan
Summary: This study investigates sequence-based predictors of RNA-binding residues (RBRs) and finds that structure-trained predictors perform well for structure-annotated proteins, while disorder-trained predictors provide accurate results for disorder-annotated proteins. However, these methods do not perform as well on opposite annotations, leading to the development of a new integrated model for improved prediction accuracy.
NUCLEIC ACIDS RESEARCH
(2023)
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Biochemistry & Molecular Biology
Jeff Gaither, Yi-Hsuan Lin, Ralf Bundschuh
Summary: The study focuses on the interactions of hundreds of RNA binding proteins in the human genome with RNA in cells, introducing RBPBind as a web-based tool for quantitatively predicting the interaction by considering the effect of RNA secondary structure on binding affinity. The tool provides a quick and easy way to obtain reliable predicted binding affinities and locations for single-stranded RNA binding proteins based solely on RNA sequence.
JOURNAL OF MOLECULAR BIOLOGY
(2022)
Article
Biochemical Research Methods
Jian Zhang, Sina Ghadermarzi, Akila Katuwawala, Lukasz Kurgan
Summary: Efforts to elucidate protein-DNA interactions at the molecular level rely on accurate predictions of DNA-binding residues in protein sequences. DNAgenie, a new predictor utilizing a custom-designed machine learning architecture, outperforms current methods in predicting residue-level interactions with A-DNA, B-DNA, and single-stranded DNA, reducing cross-predictions and generating promising leads for potential DNA-binding proteins.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Akila Katuwawala, Bi Zhao, Lukasz Kurgan
Summary: DisoLipPred is the first predictor of disordered lipid-binding residues, utilizing innovative features including transfer learning, a bypass module, and expanded inputs to improve predictive quality. The results are accurate and surpass existing tools, providing complementary predictions to current methods.
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Biochemical Research Methods
Minkyung Baek, Ryan Mchugh, Ivan Anishchenko, Hanlun Jiang, David Baker, Frank DiMaio
Summary: Protein-nucleic acid complexes have been a challenge in structure prediction, and this study introduces RoseTTAFoldNA as a method to predict their structures with high accuracy and practical value.
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Biochemistry & Molecular Biology
R. Sanchez-Garcia, J. R. Macias, C. O. S. Sorzano, J. M. Carazo, J. Segura
Summary: Computational approaches for predicting protein-protein interfaces are important for understanding protein assemblies. The performance of these methods can be improved by selecting specific training datasets. BIPSPI+ is an upgraded version trained on carefully curated datasets, providing better predictions and new functionalities.
JOURNAL OF MOLECULAR BIOLOGY
(2022)
Article
Biochemical Research Methods
Zhengfeng Wang, Xiujuan Lei
Summary: A deep learning framework CRPBsites was designed to predict the binding sites of RBPs on circRNAs, showing superior performance in experimental results and discovering highly similar binding motifs. The well-trained model successfully identified the binding sites of IGF2BP1 on circCDYL.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Biochemistry & Molecular Biology
Laiyi Fu, Yingxin Cao, Jie Wu, Qinke Peng, Qing Nie, Xiaohui Xie
Summary: UFold is a deep learning-based method for RNA secondary structure prediction, which uses a novel image-like representation of RNA sequences to achieve accurate predictions in a short time, outperforming previous methods on within-family datasets and showing similar performance on distinct RNA families.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Biochemistry & Molecular Biology
Damla Ovek, Zeynep Abali, Melisa Ece Zeylan, Ozlem Keskin, Attila Gursoy, Nurcan Tuncbag
Summary: Proteins interact through interfaces and abnormal interactions may cause diseases. Discovering small molecules that modulate protein interactions is challenging but has high therapeutic potential. Hot spot prediction is crucial for drug design.
CURRENT OPINION IN STRUCTURAL BIOLOGY
(2022)
Article
Biochemical Research Methods
Kengo Sato, Yuki Kato
Summary: Pseudoknots are important RNA structural elements involved in various biological phenomena. Current methods for secondary structure prediction considering pseudoknots are not widely available. We propose an improved version of IPknot that enables linear time calculation and automatic selection of optimal threshold parameters.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Yoochan Myung, Douglas E. Pires, David B. Ascher
Summary: The study developed a machine learning method CSM-AB capable of predicting antibody-antigen binding affinity and accurately ranking near-native poses, showing promising results for the development of new immunotherapies.
Article
Biochemistry & Molecular Biology
Ankita Agarwal, Kunal Singh, Shri Kant, Ranjit Prasad Bahadur
Summary: RNA-protein interactions play important roles in cellular machineries, but the molecular mechanism is still unclear. Study of binding interfaces is crucial for understanding molecular functioning and aberrations. Efficient computational algorithms are needed to identify protein-binding nucleotides in RNA with limited structural data compared to sequence data.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2022)
Article
Medicine, General & Internal
Qian-Rong Huang, Jian-Wen Li, Xin-Bin Pan
Summary: This study identified 27 RBPs associated with GBM prognosis and constructed a 6-RPBs signature, which effectively predicted the prognosis of GBM. Based on a nomogram and Kaplan-Meier curves, high-risk score was correlated with poor prognosis.
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Plant Sciences
Marianne C. Kramer, Hee Jong Kim, Kyle R. Palos, Benjamin A. Garcia, Eric Lyons, Mark A. Beilstein, Andrew D. L. Nelson, Brian D. Gregory
Summary: This article investigates a previously unstudied group of lncRNAs, lncCOBRA, and demonstrates that one member, lncCOBRA1, shows tissue and developmental specific expression in Arabidopsis thaliana. It is shown that plants lacking lncCOBRA1 exhibit delayed germination and stunted growth, indicating the important role of lncCOBRA1 in plant development.
FRONTIERS IN PLANT SCIENCE
(2022)
Article
Biochemistry & Molecular Biology
Anneke Brummer, Rene Dreos, Ana Claudia Marques, Sven Bergmann
Summary: This study analyzes the sequence features of hindered translation in lincRNA sequences from different eukaryotes and proposes that these features may hinder translation efficiency in species under stronger selection and in specific cell types in humans. The identified sequence signatures may improve the prediction of coding and noncoding lincRNAs in different cell types.
MOLECULAR BIOLOGY AND EVOLUTION
(2022)
Review
Plant Sciences
Susan Jones, Amanda Baizan-Edge, Stuart MacFarlane, Lesley Torrance
FRONTIERS IN PLANT SCIENCE
(2017)
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Plant Sciences
Graham H. Cowan, Alison G. Roberts, Susan Jones, Pankaj Kumar, Pruthvi B. Kalyandurg, Jose F. Gil, Eugene I. Savenkov, Piers A. Hemsley, Lesley Torrance
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Biology
Ruth V. Spriggs, Susan Jones
COMPUTATIONAL BIOLOGY AND CHEMISTRY
(2009)
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Biochemical Research Methods
DJ Winzor, S Jones, SE Harding
ANALYTICAL BIOCHEMISTRY
(2004)
Review
Biochemistry & Molecular Biology
S Jones, JM Thornton
CURRENT OPINION IN CHEMICAL BIOLOGY
(2004)
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Biochemistry & Molecular Biology
S Jones, HP Shanahan, HM Berman, JM Thornton
NUCLEIC ACIDS RESEARCH
(2003)
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Biochemistry & Molecular Biology
S Jones, JM Thornton
COMPARATIVE AND FUNCTIONAL GENOMICS
(2003)
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Biochemistry & Molecular Biology
S Jones, JA Barker, I Nobeli, JM Thornton
NUCLEIC ACIDS RESEARCH
(2003)
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Biochemistry & Molecular Biology
B Carrasco, JG de la Torre, KG Davis, S Jones, D Athwal, C Walters, DR Burton, SE Harding
BIOPHYSICAL CHEMISTRY
(2001)
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Biochemistry & Molecular Biology
S Jones, DTA Daley, NM Luscombe, HM Berman, JM Thornton
NUCLEIC ACIDS RESEARCH
(2001)
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Biochemistry & Molecular Biology
HP Shanahan, MA Garcia, S Jones, JM Thornton
NUCLEIC ACIDS RESEARCH
(2004)