Article
Chemistry, Multidisciplinary
Jin Tao, Kelly A. Brayton, Shira L. Broschat
Summary: This study introduces a novel approach using ensemble learning and natural language processing to verify protein annotation, ensuring accuracy. The model achieves good results in experiments and outperforms other models.
APPLIED SCIENCES-BASEL
(2021)
Article
Biochemical Research Methods
Jun-Jie Zheng, Po-Wen Wang, Tzu-Wen Huang, Yao-Jong Yang, Hua-Sheng Chiu, Pavel Sumazin, Ting-Wen Chen
Summary: Microbiota analyses play a crucial role in health and science, but the available tools require programming skills and statistical knowledge. MOCHI, a GUI tool for microbiota amplicon sequencing analysis, can help practitioners with real-time analysis and data visualization.
Article
Mathematical & Computational Biology
Baiyang Feng, Jing Gao
Summary: This study utilized text mining tools to extract relevant entities and association relationships from a large number of anthrax biomedical literature, and constructed an anthrax knowledge graph. An interactive visualized knowledge portal was developed based on the knowledge graph. The portal provides rich and authentic knowledge in various forms, facilitating efficient research.
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
(2022)
Article
Chemistry, Multidisciplinary
Jing Chen, Qun Zhao, Hang Gao, Lili Zhao, Huiying Chu, Yichu Shan, Zhen Liang, Yukui Zhang, Lihua Zhang
Summary: Chemical cross-linking mass spectrometry (CXMS) is a powerful technology for analyzing protein complexes. However, in vivo CXMS studies have been limited by cross-linking biocompatibility and data analysis. In this study, a glycosidic bond-based MS-cleavable cross-linker called trehalose disuccinimidyl ester (TDS) was designed and synthesized, which simplified the cross-linked peptides into conventional single peptides via selective cleavage. TDS showed high biocompatibility and accuracy, enhancing the cross-linking identification accuracy and throughput.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2023)
Article
Biochemical Research Methods
Kaitao Wu, Lexiang Wang, Bo Liu, Yang Liu, Yadong Wang, Junyi Li
Summary: Using computational methods to predict protein function effectively remains a challenge. Methods based on single species or single data source have limitations: different species require different models, and single perspective methods such as using Protein-Protein Interaction network only consider the protein environment and ignore intrinsic characteristics of protein sequences. To solve these problems, we propose PSPGO, a cross-species heterogeneous network propagation method based on graph attention mechanism, which can predict gene ontology terms by propagating feature and label information on sequence similarity and PPI networks. Our model is evaluated on a large multi-species dataset and compared with state-of-the-art methods, showing good performance.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Biochemistry & Molecular Biology
Spyros Tastsoglou, Giorgos Skoufos, Marios Miliotis, Dimitra Karagkouni, Ioannis Koutsoukos, Anna Karavangeli, Filippos S. Kardaras, Artemis G. Hatzigeorgiou
Summary: DIANA-miRPath is an online miRNA analysis platform that allows exploration of combined miRNA effects through predicted or experimentally supported miRNA interactions. Its latest version introduces a customizable target-based miRNA functional analysis engine, enriched with interaction, annotation, and parameterization options. The platform integrates various datasets and enables enrichment analysis on GO terms, pathways, and expression data for a wide range of states. Additionally, it provides a module for utilizing CRISPR knock-out screen datasets to identify miRNAs with potentially crucial roles.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Microbiology
Morgan N. Price, Adam P. Arkin
Summary: To assist biologists in studying the functional residues of proteins, we developed two interactive web-based tools, SitesBLAST and Sites on a Tree. These tools identify homologs with known functional residues and show whether these residues are conserved. Additionally, Sites on a Tree visually displays how functional residues vary across a protein family. These tools provide valuable insights for predicting protein function and comparing key residues among similar proteins.
Article
Biochemical Research Methods
Jiyu Chen, Nicholas Geard, Justin Zobel, Karin Verspoor
Summary: Two models built using our method achieved high precision for distinct annotation consistency identification tasks and were robust to updates in the GO vocabulary. Our approach demonstrates clear value for human-in-the-loop curation scenarios.
BMC BIOINFORMATICS
(2021)
Article
Multidisciplinary Sciences
Marloes Heijne, Martina Jelocnik, Alexander Umanets, Michael S. M. Brouwer, Annemieke Dinkla, Frank Harders, Lucien J. M. van Keulen, Hendrik Jan Roest, Famke Schaafsma, Francisca C. Velkers, Jeanet A. van der Goot, Yvonne Pannekoek, Ad P. Koets
Summary: Chlamydia gallinacea, a newly added bacterium in the family Chlamydiaceae, is genetically diverse and suspected to cause pneumonia in poultry and slaughterhouse workers. It was isolated from healthy chickens in this study, with infection experiments showing mortality in embryonated eggs, indicating it may be an opportunistic pathogen. Comparisons with Chlamydia psittaci confirmed the presence of virulence factors in C. gallinacea genomes but with fewer orthologues or paralogs.
SCIENTIFIC REPORTS
(2021)
Article
Biochemistry & Molecular Biology
Maxim Kuleshov, Zhuorui Xie, Alexandra B. K. London, Janice Yang, John Erol Evangelista, Alexander Lachmann, Ingrid Shu, Denis Torre, Avi Ma'ayan
Summary: KEA3 is a webserver application used to predict upstream kinases and analyze data from proteomics and phosphoproteomics studies. The background database of KEA3 contains measured and predicted kinase-substrate interactions. Studies show that integrating kinase-substrate and kinase-protein interactions across data sources improves the recovery of the expected kinase.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Virology
Carla Zannella, Annalisa Chianese, Giuseppe Greco, Biagio Santella, Giuseppe Squillaci, Alessandra Monti, Nunzianna Doti, Giuseppina Sanna, Aldo Manzin, Alessandra Morana, Anna De Filippis, Gianni D'Angelo, Francesco Palmieri, Gianluigi Franci, Massimiliano Galdiero
Summary: The rapid spread of COVID-19 has led to the search for new therapeutic and prophylactic treatments. This study investigates the use of synthetic peptides to inhibit the infection of HCoV-OC43 and SARS-CoV-2 by binding to the Spike protein. The peptides show high efficiency, low toxicity, and resistance to proteases, making them promising antiviral candidates.
Review
Chemistry, Multidisciplinary
Jie Li, Keren Chen, Longjiao Zhu, Xiangyang Li, Changmo Li, Qiaoying Chang, Wentao Xu
Summary: This review summarizes the point-of-care detection of pesticides based on multiple recognition methods, aiming to address the issues of environmental pollution and human health risks caused by excessive pesticide use.
FRONTIERS IN CHEMISTRY
(2022)
Review
Chemistry, Multidisciplinary
Ruben Laplaza, Francesca Peccati, Roberto A. Boto, Chaoyu Quan, Alessandra Carbone, Jean-Philip Piquemal, Yvon Maday, Julia Contreras-Garcia
Summary: Noncovalent interactions are crucial but challenging to accurately treat. The NCI index has been successfully used to identify, analyze, and understand these interactions across various systems, showcasing advancements in their fast and intuitive identification in real space.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE
(2021)
Article
Computer Science, Information Systems
Mariusz Rafalo
Summary: Much of modern medical research relies on statistics and machine learning techniques. Cross validation is an important tool for measuring the effectiveness of models and comparing them. This paper presents an analysis of cross validation methods using a logistic regression model and finds that high variance in the developed models is a main reason for the lack of a single threshold value. The research also suggests that the choice of validation technique influences both the measurement of model quality and the determination of threshold values.
Article
Chemistry, Multidisciplinary
Chiranjit Mahato, Sneha Menon, Abhishek Singh, Syed Pavel Afrose, Jagannath Mondal, Dibyendu Das
Summary: In this study, it is reported that short peptides can expose multiple catalytic residues through cross-beta stacking, resembling the advanced binding pockets of enzymes. These binding pockets with multiple catalytic residues enhance substrate binding and facilitate kinetically unfavorable chemical reactions. The solvent-exposed guanidinium and imidazole groups on the cross-beta microphases synergistically bind and hydrolyze nucleases and phosphatase substrates. Mutation of either histidine or arginine significantly decreases hydrolysis rate. These findings not only support the hypothesis of short amyloid peptides as the earliest protein folds but also suggest their interactions with nucleic acid congeners, indicating the symbiotic relationships between biopolymers that contributed to the chemical emergence of life.
Article
Oncology
Margaret M. Lee, Andrew MacKinlay, Christine Semira, Christine Schieber, Antonio Jose Jimeno Yepes, Belinda Lee, Rachel Wong, Chathurika K. H. Hettiarachchige, Natalie Gunn, Jeanne Tie, Hui-Li Wong, Iain Skinner, Ian T. Jones, James Keck, Suzanne Kosmider, Ben Tran, Kathryn Field, Peter Gibbs
CLINICAL COLORECTAL CANCER
(2018)
Article
Geochemistry & Geophysics
Jianbin Tang, Benjamin Scott Mashford, Antonio Jimeno Yepes
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2018)
Article
Biochemical Research Methods
Peiliang Lou, Antonio Jimeno Yepes, Zai Zhang, Qinghua Zheng, Xiangrong Zhang, Chen Li
Article
Public, Environmental & Occupational Health
Ying Li, Antonio Jimeno Yepes, Cao Xiao
Article
Computer Science, Interdisciplinary Applications
Corey Sutphin, Kahyun Lee, Antonio Jimeno Yepes, Ozlem Uzuner, Bridget T. McInnes
JOURNAL OF BIOMEDICAL INFORMATICS
(2020)
Article
Health Care Sciences & Services
Simon Suster, Timothy Baldwin, Jey Han Lau, Antonio Jimeno Yepes, David Martinez Iraola, Yulia Otmakhova, Karin Verspoor
Summary: The study proposes a quality assessment task that provides an overall quality rating for each body of evidence (BoE) and justification for different quality criteria. A machine learning system (EvidenceGRADEr) is developed to automate the quality assessment process using a new dataset. The results show that the system performs well for some quality criteria but struggles with others due to limited data availability. This technology has the potential to reduce reviewer workload and expedite evidence synthesis.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2023)
Article
Mathematical & Computational Biology
Qingyu Chen, Alexis Allot, Robert Leaman, Rezarta Islamaj, Jingcheng Du, Li Fang, Kai Wang, Shuo Xu, Yuefu Zhang, Parsa Bagherzadeh, Sabine Bergler, Aakash Bhatnagar, Nidhir Bhavsar, Yung-Chun Chang, Sheng-Jie Lin, Wentai Tang, Hongtong Zhang, Ilija Tavchioski, Senja Pollak, Shubo Tian, Jinfeng Zhang, Yulia Otmakhova, Antonio Jimeno Yepes, Hang Dong, Honghan Wu, Richard Dufour, Yanis Labrak, Niladri Chatterjee, Kushagri Tandon, Frejus A. A. Laleye, Loic Rakotoson, Emmanuele Chersoni, Jinghang Gu, Annemarie Friedrich, Subhash Chandra Pujari, Mariia Chizhikova, Naveen Sivadasan, V. G. Saipradeep, Zhiyong Lu
Summary: The COVID-19 pandemic has had a severe impact on global society, leading to a rapid growth in related literature. To address the challenges of manual curation and interpretation, the BioCreative LitCovid track called for a community effort to automate topic annotation. Nineteen teams participated, achieving higher scores compared to existing methods.
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Simon Suster, Karin Verspoor, Timothy Baldwin, Jey Han Lau, Antonio Jimeno Yepes, David Martinez Iraola, Yulia Otmakhova
Summary: The COVID-19 pandemic has increased demand for tools that efficiently explore biomedical literature. Filtering results using clinically-relevant concepts and their relations can improve precision and increase the likelihood of users being exposed to more relevant documents, as demonstrated in an analysis using the TREC-COVID dataset.
2021 IEEE 9TH INTERNATIONAL CONFERENCE ON HEALTHCARE INFORMATICS (ICHI 2021)
(2021)
Article
Audiology & Speech-Language Pathology
Elaheh Shafieibavani, Benjamin Goudey, Isabell Kiral, Peter Zhong, Antonio Jimeno-Yepes, Annalisa Swan, Manoj Gambhir, Andreas Buechner, Eugen Kludt, Robert H. Eikelboom, Cathy Sucher, Rene H. Gifford, Riaan Rottier, Kerrie Plant, Hamideh Anjomshoa
Summary: While machine learning shows better predictive accuracy for cochlear implant outcomes compared to traditional statistical methods, there are still limitations in overall accuracy. The study conducted is the largest retrospective study on cochlear implant outcomes to date, highlighting the superior performance of machine learning models in predicting word recognition scores.
Proceedings Paper
Computer Science, Artificial Intelligence
Antonio Jimeno Yepes, Peter Zhong, Douglas Burdick
Summary: Scientific literature contains important information for cutting-edge innovations, and advancements in natural language processing have enabled automated information extraction, despite challenges such as unstructured PDF formats and non-natural language content. The ICDAR 2021 Scientific Literature Parsing Competition aims to drive document understanding advances and has shown impressive performance in tasks related to document layout and table recognition.
DOCUMENT ANALYSIS AND RECOGNITION, ICDAR 2021, PT IV
(2021)
Article
Audiology & Speech-Language Pathology
Benjamin Goudey, Kerrie Plant, Isabell Kiral, Antonio Jimeno-Yepes, Annalisa Swan, Manoj Gambhir, Andreas Buechner, Eugen Kludt, Robert H. Eikelboom, Cathy Sucher, Rene H. Gifford, Riaan Rottier, Hamideh Anjomshoa
Summary: This study investigates the association between 21 preoperative factors and speech recognition one year after cochlear implantation, providing evidence of 17 statistically significant associations. Despite the large sample size, the variance explained by the models remains modest. Additionally, a novel statistical interaction indicates that the duration of deafness in the implanted ear has a stronger impact on hearing outcome when considered relative to a candidate's age.
Article
Biochemical Research Methods
Peiliang Lou, YuXin Dong, Antonio Jimeno Yepes, Chen Li
Summary: This study introduces a new bio-entity representation learning model ERBK, which encodes axioms and definitions using knowledge graph embedding method and deep convolutional neural network respectively. Experimental results show that ERBK outperforms existing methods in predicting protein-protein interactions and gene-disease associations, and maintains promising performance under zero-shot circumstances.
Proceedings Paper
Computer Science, Artificial Intelligence
Elaheh ShafieiBavani, Antonio Jimeno Yepes, Xu Zhong, David Martinez Iraola
19TH SIGBIOMED WORKSHOP ON BIOMEDICAL LANGUAGE PROCESSING (BIONLP 2020)
(2020)
Article
Medicine, General & Internal
Thomas Schaffter, Diana S. M. Buist, Christoph Lee, Yaroslav Nikulin, Dezso Ribli, Yuanfang Guan, William Lotter, Zequn Jie, Hao Du, Sijia Wang, Jiashi Feng, Mengling Feng, Hyo-Eun Kim, Francisco Albiol, Alberto Albiol, Stephen Morrell, Zbigniew Wojna, Mehmet Eren Ahsen, Umar Asif, Antonio Jimeno Yepes, Shivanthan Yohanandan, Simona Rabinovici-Cohen, Darvin Yi, Bruce Hoff, Thomas Yu, Elias Chaibub Neto, Daniel L. Rubin, Peter Lindholm, Laurie R. Margolies, Russell Bailey McBride, Joseph H. Rothstein, Weiva Sieh, Rami Ben-Ari, Stefan Harrer, Andrew Trister, Stephen Friend, Thea Norman, Berkman Sahiner, Fredrik Strand, Justin Guinney, Gustavo Stolovitzky
Proceedings Paper
Computer Science, Artificial Intelligence
Rachel Bawden, K. Bretonnel Cohen, Cristian Grozea, Antonio Jimeno Yepes, Madeleine Kittner, Martin Krallinger, Nancy Mah, Aurelie Neveol, Mariana Neves, Felipe Soares, Amy Siu, Karin Verspoor, Maika Vicente Navarro
FOURTH CONFERENCE ON MACHINE TRANSLATION (WMT 2019), VOL 3: SHARED TASK PAPERS, DAY 2
(2019)