Article
Biochemistry & Molecular Biology
Wang Kang, Tong Jin, Tao Zhang, Shuai Ma, Haoteng Yan, Zunpeng Liu, Zhejun Ji, Yusheng Cai, Si Wang, Moshi Song, Jie Ren, Baoyang Hu, Qi Zhou, Weiqi Zhang, Jing Qu, Yiming Bao, Guang-Hui Liu
Summary: Regeneration plays a crucial role in biological development and damage repair, but its capacity declines with age. There is currently a lack of comprehensive database to collect and standardize the abundant data generated in regeneration research.
NUCLEIC ACIDS RESEARCH
(2022)
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
Computer Science, Artificial Intelligence
Jose F. Aldana-Martin, Jose Garcia-Nieto, Maria del Mar Roldan-Garcia, Jose F. Aldana-Montes
Summary: Remote sensing technology provides a technological framework for advanced applications in various fields, with Earth Observation becoming increasingly important. Knowledge-driven approaches remain a challenge in remote sensing, with semantic technologies showing high success in knowledge representation in the Earth Observation domain.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Shital Kakad, Sudhir Dhage
Summary: This paper explores ontology construction model under cross-domain application, focusing on data filtering and data annotation decision-making processes. The process involves Jaccard Similarity Evaluation, data filtering, outlier detection, semantic annotation, and clustering to form ontology clusters.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Multidisciplinary Sciences
Jianfeng Jin, Yuxin Zhao, Guoqiang Zhang, Zhixiang Pan, Feng Zhang
Summary: This study presents the first chromosome-level genome of Entomobrya proxima, the largest superfamily of Collembola, using PacBio long reads, Illumina short reads, and Hi-C data. The genome has a size of 362.37 Mb, with a scaffold N50 size of 57.67 Mb, and 97.12% (351.95 Mb) of the assembly is located on six chromosomes. The analysis revealed important expansions in gene families associated with detoxification and metabolism in E. proxima, as well as strong chromosomal synteny between E. proxima and Sinella curviseta. This research provides valuable genomic information for understanding the evolution and ecology of Collembola.
Article
Biochemical Research Methods
Ziyin Xin, Yujun Cai, Louis T. Dang, Hannah M. S. Burke, Jerico Revote, Natalie Charitakis, Denis Bienroth, Hieu T. Nim, Yuan-Fang Li, Mirana Ramialison
Summary: MonaGO is a web-based visualization system that allows biologists to perform GO enrichment analysis and visualize the results in an intuitive, interactive, and responsive manner. It supports various input formats and provides customizable display options.
BMC BIOINFORMATICS
(2022)
Review
Medicine, Research & Experimental
Lillian T. Tatka, Lucian P. Smith, Joseph L. Hellerstein, Herbert M. Sauro
Summary: Computational models are increasingly used in high-impact decision making in science, engineering, and medicine. NASA, FDA, and EMA have developed standards to promote and assess the credibility of computational models. However, there is a need for specific credibility standards in the narrower domain of systems biology models.
JOURNAL OF TRANSLATIONAL MEDICINE
(2023)
Article
Construction & Building Technology
Jingming Li, Nianping Li, Bao Yue, Rui Yan, Kushnazarov Farruh, Anbang Li, Kehua Li
Summary: This paper investigates the semantic description of Variable Refrigerant Flow systems in building metadata standards and develops a corresponding data management framework. Experimental results show that using the semantic model and service framework can reduce manpower and data analysis time.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Biochemistry & Molecular Biology
Rodrigo Honorato, Panagiotis Koukos, Brian Jimenez-Garcia, Andrei Tsaregorodtsev, Marco Verlato, Andrea Giachetti, Antonio Rosato, Alexandre M. J. J. Bonvin
Summary: Structural biology focuses on studying the structural and dynamic properties of biological macromolecules at atomic level, which is crucial for understanding cellular processes and has applications in health and food sciences. The WeNMR project has provided web-based services and high throughput computing infrastructure to over 23,000 users worldwide for 10 years, facilitating complex workflows in structural biology research.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2021)
Article
Biochemical Research Methods
Adrien Rougny, Vasundra Toure, John Albanese, Dagmar Waltemath, Denis Shirshov, Anatoly Sorokin, Gary D. Bader, Michael L. Blinov, Alexander Mazein
Summary: SBGN has become the main standard for representing molecular networks graphically in scientific publications, but the process of learning and using it for building large maps can be tedious. To address this, SBGN bricks and the Bricks Ontology (BKO) have been introduced to enhance efficiency in template-based construction and semantic annotation of molecular networks. These resources can be freely accessed and downloaded at sbgnbricks.org.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Computer Science, Information Systems
Shahid Yousaf, Hafiz Mahfooz Ul Haque, Abbas Khalid, Muhammad Adnan Hashmi, Eraj Khan
Summary: This paper proposes a context-aware intelligent decision support formalism to assist cognitively impaired individuals in managing their daily activities. By contextualizing information from the environment using a semantic knowledge-based framework, a context-aware multi-agent system can be created to autonomously plan user activities and notify users accordingly.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Computer Science, Information Systems
Daniele Spoladore, Elena Pessot
Summary: This paper highlights the importance of using ontology engineering methodologies in the healthcare sector, identifies key issues in existing methods, and proposes specific areas of focus. Through three use cases in health-related fields, the paper showcases approaches to addressing these issues in the development of collaborative ontology engineering methodologies supporting Decision Support Systems.
Article
Entomology
Surya Saha, Amanda M. Cooksey, Anna K. Childers, Monica F. Poelchau, Fiona M. McCarthy
Summary: This article presents a fast workflow for functional annotation of whole proteomes to generate Gene Ontology and pathways information, with applications to diverse arthropod genomes and comparisons to reference genomes. The performance of the predictions remains consistent across various arthropod genomes with different assembly and annotation qualities.
Article
Computer Science, Hardware & Architecture
Vasanthi Raghupathy, Osamah Ibrahim Khalaf, Carlos Andres Tavera Romero, Sudhakar Sengan, Dilip Kumar Sharma
Summary: Computing has become more invisible, widespread and ubiquitous with the advent of IoT and WoT. Users can freely switch between devices and interact continuously in a wide environment. Interoperability across platforms is necessary for linking various devices in a heterogeneous environment.
COMPUTER SYSTEMS SCIENCE AND ENGINEERING
(2022)
Article
Pharmacology & Pharmacy
Pukar Khanal, Vishal S. Patil, Vishwambhar V. Bhandare, Priyanka P. Patil, B. M. Patil, Prarambh S. R. Dwivedi, Kunal Bhattacharya, Darasaguppe R. Harish, Subarna Roy
Summary: The aim of this study was to investigate the mechanism of action of diosgenin against breast cancer using system biology tools and experimental validation. Diosgenin-regulated domains associated with breast cancer were identified and diosgenin-protein-pathway associations were established. Molecular docking and dynamics simulations confirmed the binding affinity of diosgenin with key proteins, and functional assays validated its effects on cell proliferation, cytotoxicity, and the Warburg effect.
FRONTIERS IN PHARMACOLOGY
(2023)
Article
Cell Biology
Piero Dalle Pezze, Eleftherios Karanasios, Varvara Kandia, Maria Manifava, Simon A. Walker, Nicolas Gambardella Le Novere, Nicholas T. Ktistakis
Summary: The study found that the translocation of ATG13 during autophagy is influenced by different stimuli and drugs, with multiple translocations observed during mitophagy. The mathematical model supports the hypothesis that the number of ATG13 translocations is directly proportional to the diameter of the targeted mitochondrial fragments, providing new insights into the early dynamics of selective and nonselective autophagy.
Article
Health Care Sciences & Services
Kai He, Lixia Yao, JiaWei Zhang, Yufei Li, Chen Li
Summary: Researchers utilized online obituary data to construct genealogical knowledge graphs, successfully extracting and assembling family relationship data through a multitask neural network model, providing more comprehensive and accurate support for biomedical research.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2021)
Article
Mathematical & Computational Biology
Hasan Baig, Pedro Fontanarossa, Vishwesh Kulkarni, James McLaughlin, Prashant Vaidyanathan, Bryan Bartley, Shyam Bhakta, Swapnil Bhatia, Mike Bissell, Kevin Clancy, Robert Sidney Cox, Angel Goni Moreno, Thomas Gorochowski, Raik Grunberg, Jihwan Lee, Augustin Luna, Curtis Madsen, Goksel Misirli, Tramy Nguyen, Nicolas Le Novere, Zachary Palchick, Matthew Pocock, Nicholas Roehner, Herbert Sauro, James Scott-Brown, John T. Sexton, Guy-Bart Stan, Jeffrey J. Tabor, Logan Terry, Marta Vazquez Vilar, Christopher A. Voigt, Anil Wipat, David Zong, Zach Zundel, Jacob Beal, Chris Myers
Summary: SBOL Visual is a standard for organizing diagrams in biological engineering, and the latest version 2.3 includes higher-level interactions and more visual options for genetic designs.
JOURNAL OF INTEGRATIVE BIOINFORMATICS
(2021)
Article
Biochemistry & Molecular Biology
Melanie Courtot, Dipayan Gupta, Isuru Liyanage, Fuqi Xu, Tony Burdett
Summary: The BioSamples database at EMBL-EBI serves as the central institutional repository for sample metadata storage and emphasizes on improving data quality and adhering to FAIR principles. In 2021, the database handled user community requirements through exemplar use cases, such as enhancing sample findability, improving data management practices, and supporting complex multi-omics data integration for COVID-19 research.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Mathematical & Computational Biology
Rebecca Jackson, Nicolas Matentzoglu, James A. Overton, Randi Vita, James P. Balhoff, Pier Luigi Buttigieg, Seth Carbon, Melanie Courtot, Alexander D. Diehl, Damion M. Dooley, William D. Duncan, Nomi L. Harris, Melissa A. Haendel, Suzanna E. Lewis, Darren A. Natale, David Osumi-Sutherland, Alan Ruttenberg, Lynn M. Schriml, Barry Smith, Christian J. Stoeckert, Nicole A. Vasilevsky, Ramona L. Walls, Jie Zheng, Christopher J. Mungall, Bjoern Peters
Summary: Biological ontologies are used to organize and interpret data from experiments, but integrating multiple ontologies can lead to compatibility issues. The OBO Foundry aims to promote the development and sharing of ontologies through a set of principles. Researchers have improved ontology quality and interoperability by encoding principles as operational rules and implementing automated validation checks.
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
(2021)
Article
Multidisciplinary Sciences
Peiliang Lou, Chunbao Wang, Ruifeng Guo, Lixia Yao, Guanjun Zhang, Jun Yang, Yong Yuan, Yuxin Dong, Zeyu Gao, Tieliang Gong, Chen Li
Summary: The study of histopathological phenotypes is crucial for cancer research and medicine. However, the lack of a standardized format and controlled vocabulary hinders the large-scale implementation of histopathological features. To address this issue, we propose the Histopathology Markup Language (HistoML) and a controlled vocabulary (Histopathology Ontology) to objectively describe and query histopathological phenotypes.
Article
Computer Science, Information Systems
Jiangbo Shi, Tieliang Gong, Chunbao Wang, Chen Li
Summary: Accurate tissue segmentation in histopathological images is crucial for advancing precision pathology. We propose a semi-supervised pixel contrastive learning framework (SSPCL) to mimic the pathologist's diagnosis process and model the semantic relation of the whole slide image. SSPCL includes an uncertainty-guided mutual dual consistency learning module (UMDC) and a cross image pixel-contrastive learning module (CIPC). Experimental results show that SSPCL significantly reduces labeling cost and achieves accurate quantitation of tissues, outperforming state-of-the-art methods by up to 5.0% in mDice.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Kai He, Yucheng Huang, Rui Mao, Tieliang Gong, Chen Li, Erik Cambria
Summary: This paper proposes a virtual prompt pre-training method that incorporates the virtual prompt into PLM parameters to achieve entity-relation-aware pre-training. The proposed method provides robust initialization for prompt encoding and avoids the labor-intensive and subjective issues in label word mapping and prompt template engineering.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Yuxin Dong, Tieliang Gong, Shujian Yu, Chen Li
Summary: The matrix-based Renyi's entropy is widely used in statistical learning and inference tasks for directly measuring information quantities from given data without expensive probability density estimation. However, its exact calculation requires access to the eigenspectrum of a semi-positive definite matrix A, resulting in a time complexity of O(n(3)) for large-scale applications. To address this issue, this paper proposes stochastic trace approximations, which convert the entropy approximation to a matrix-vector multiplication problem, reducing the complexity to O(n(2)sm), where s and m denote the number of vector queries and the polynomial order respectively. The developed approximations are theoretically guaranteed and validated through simulations and real-world applications, showing remarkable speedup with negligible loss in accuracy.
IEEE TRANSACTIONS ON INFORMATION THEORY
(2023)
Article
Computer Science, Interdisciplinary Applications
Jiangbo Shi, Lufei Tang, Yang Li, Xianli Zhang, Zeyu Gao, Yefeng Zheng, Chunbao Wang, Tieliang Gong, Chen Li
Summary: This paper presents a structure-aware hierarchical graph-based multi-instance learning framework (SGMF) for the pathological primary tumor (pT) stage. By introducing structure-aware hierarchical graph (SAHG) and hierarchical attention-based graph representation (HAGR) network, accurate classification of pT staging is achieved.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2023)
Article
Computer Science, Artificial Intelligence
Kai He, Rui Mao, Tieliang Gong, Chen Li, Erik Cambria
Summary: The study proposes a meta-based self-training method for aspect-based sentiment analysis (ABSA). By generating pseudo-labels and controlling convergence rates, the method improves model performance and accuracy in fine-grained sentiment analysis.
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
(2023)
Article
Computer Science, Interdisciplinary Applications
Jiangbo Shi, Lufei Tang, Zeyu Gao, Yang Li, Chunbao Wang, Tieliang Gong, Chen Li, Huazhu Fu
Summary: This study proposes a Multi-scale Graph Transformer (MG-Trans) with an information bottleneck for processing megapixel-sized whole slide images in digital pathology. The MG-Trans overcomes the limitations of input redundancy and insufficient spatial relations modeling through patch anchoring, dynamic structure information learning, and multi-scale information bottleneck modules. The proposed method also introduces a semantic consistency loss to stabilize the model training.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2023)
Article
Computer Science, Artificial Intelligence
Yuxin Dong, Tieliang Gong, Hong Chen, Chen Li
Summary: The matrix-based Renyi's entropy (MBRE) is introduced as a substitute for original Renyi's entropy, avoiding the costly density estimation step. To overcome the computational cost issue in large-scale applications, the study proposes a static MBRE estimator combined with a variance reduction criterion to develop randomized approximations for the target entropy, achieving high accuracy with lower query complexity by utilizing historical estimation results.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Kai He, Rui Mao, Yucheng Huang, Tieliang Gong, Chen Li, Erik Cambria
Summary: In this paper, a prompt-based contrastive learning method is proposed for few-shot NER tasks. The method leverages external knowledge to initialize semantic anchors and optimizes prompts and sentence embeddings with a proposed semantic-enhanced contrastive loss. The method outperforms traditional contrastive learning methods in few-shot scenarios and effectively addresses the issues in conventional methods.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Biochemistry & Molecular Biology
Peter W. Harrison, Alisha Ahamed, Raheela Aslam, Blaise T. F. Alako, Josephine Burgin, Nicola Buso, Melanie Courtot, Jun Fan, Dipayan Gupta, Muhammad Haseeb, Sam Holt, Talal Ibrahim, Eugene Ivanov, Suran Jayathilaka, Vishnukumar Balavenkataraman Kadhirvelu, Manish Kumar, Rodrigo Lopez, Simon Kay, Rasko Leinonen, Xin Liu, Colman O'Cathail, Amir Pakseresht, Youngmi Park, Stephane Pesant, Nadim Rahman, Jeena Rajan, Alexey Sokolov, Senthilnathan Vijayaraja, Zahra Waheed, Ahmad Zyoud, Tony Burdett, Guy Cochrane
Summary: The European Nucleotide Archive (ENA) has been dedicated to freely archiving and presenting global public sequencing data for nearly 40 years, benefiting the entire scientific community and accelerating global research efforts. In 2020, major developments to ENA services and content included the release of an updated ENA browser, modernization of the release process, and collaborations with specific research communities for data coordination.
NUCLEIC ACIDS RESEARCH
(2021)
