Article
Chemistry, Multidisciplinary
Alexandros Kanterakis, Nikos Kanakaris, Manos Koutoulakis, Konstantina Pitianou, Nikos Karacapilidis, Lefteris Koumakis, George Potamias
Summary: This paper discusses the resources and technical challenges of semantic annotation tools for biomedical text, aiming to create ready-to-install and run Research Objects to support biomedical text analysis.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Information Systems
Ying Hu, Yanping Chen, Ruizhang Huang, Yongbin Qin, Qinghua Zheng
Summary: Biomedical relation extraction aims to extract the interactive relations between biomedical entities in a sentence. This study proposes a hierarchical convolutional model to address the semantic overlapping and data imbalance problems. The model encodes both local contextual features and global semantic dependencies, enhancing the discriminability of the neural network for biomedical relation extraction.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Editorial Material
Biochemistry & Molecular Biology
David Horsfall, Jonah Cool, Simon Hettrick, Angela Oliveira Pisco, Neil Chue Hong, Muzlifah Haniffa
Summary: Research software engineering is crucial for data-driven biomedical research, yet its significance is often underestimated and misunderstood.
Article
Environmental Studies
Yong Guo, Fuqiang Yang
Summary: This study proposes a three-step approach to understand the current status and development trend of mining safety research in China, including literature extraction and screening, bibliometric analysis, and discussion. By analyzing 1814 extracted articles from the Web of Science Core Collection, the study explores influential authors/institutions, collaborations, keywords, citations, and funding agencies. The results indicate an increasing trend in mining safety research, focusing on topics such as gas hazards, rockburst, water inrush, and thermodynamic disasters. The study also identifies limitations and proposes future research directions, including intelligent mines, safety information mines, and quantitative analysis of deep mining accidents mechanisms.
Article
Computer Science, Information Systems
Xingyu Wu, Zhenchao Tao, Bingbing Jiang, Tianhao Wu, Xin Wang, Huanhuan Chen
Summary: Machine learning has been successful in analyzing biomedical data. However, the lack of samples in the biomedical field poses challenges for traditional variable selection algorithms. This paper proposes a method that utilizes domain knowledge to overcome this issue and demonstrates its effectiveness.
INFORMATION SCIENCES
(2022)
Article
Engineering, Multidisciplinary
Md Shazzadul Islam, S. M. Kayser Azam, A. K. M. Zakir Hossain, Muhammad I. Ibrahimy, S. M. A. Motakabber
Summary: This article proposes a low profile planar monopole antenna on flexible substrate. The antenna operates within 7-14 GHz with low return loss, excellent VSWR, and high radiation efficiency. It is suitable for biomedical imaging applications.
ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH
(2022)
Review
Biotechnology & Applied Microbiology
Qisong Liu, Jianghong Huang, Jiang Xia, Yujie Liang, Guangheng Li
Summary: Imaging of extracellular vesicles (EVs) plays a crucial role in understanding their biological functions and potential as therapeutics and drug delivery vehicles. Various labeling and imaging methods, such as fluorescent imaging, bioluminescent imaging, nuclear imaging, and nanoparticle-assisted imaging, have been developed to track the communication and bio-distribution of EVs. These techniques contribute to a better understanding of EV uptake mechanisms, biological functions, and pharmacokinetic properties, which are essential for their clinical application.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Yu Hu, Tiezheng Nie, Derong Shen, Yue Kou, Ge Yu
Summary: Biomedical entity alignment, consisting of entity identification and entity-concept mapping, is crucial in biomedical text mining. The proposed biomedical entity exploring model improves performance by automatically extracting semantic information and aligning entities to the knowledge base, achieving better F1 scores in both tasks.
FRONTIERS OF COMPUTER SCIENCE
(2021)
Review
Biochemical Research Methods
Sendong Zhao, Chang Su, Zhiyong Lu, Fei Wang
Summary: In recent years, there has been a rapid increase in scientific articles in the biomedical domain, leading to a high demand for biomedical literature mining techniques. Efforts from both the BMI and CS communities have focused on developing more interpretable and descriptive methods in the BMI community, while the CS community has been more focused on superior performance and generalization ability, leading to the development of more sophisticated and universal models. A review of recent advances in BLM from both communities aims to inspire new research directions.
BRIEFINGS IN BIOINFORMATICS
(2021)
Editorial Material
Biochemical Research Methods
Julian Matschinske, Nicolas Alcaraz, Arriel Benis, Martin Golebiewski, Dominik G. Grimm, Lukas Heumos, Tim Kacprowski, Olga Lazareva, Markus List, Zakaria Louadi, Josch K. Pauling, Nico Pfeifer, Richard Roettger, Veit Schwaemmle, Gregor Sturm, Alberto Traverso, Kristel Van Steen, Martiela Vaz de Freitas, Gerda Cristal Villalba Silva, Leonard Wee, Nina K. Wenke, Massimiliano Zanin, Olga Zolotareva, Jan Baumbach, David B. Blumenthal
Summary: The AIMe registry is a community-driven reporting platform for AI in biomedicine, aiming to improve the accessibility, reproducibility, and usability of biomedical AI models, and allowing future revisions by the community.
Review
Biochemical Research Methods
Xiu-Ju George Zhao, Hui Cao
Summary: This article reviews the importance of biomedical data preprocessing and efficient computing, emphasizing the need to consider application scenarios, data acquisition, and individual rights. The article summarizes the common principles, knowledge, and methods of integrated research according to the whole-pipeline processing mechanism, and proposes new directions including the integration of neuromorphic and native algorithms, the mechanism of choosing different preprocessing, analysis, and transaction methods, and the construction of an ecosystem for integrated research and clinical diagnosis and treatment.
BRIEFINGS IN BIOINFORMATICS
(2022)
Review
Biochemical Research Methods
Mohamed Nadif, Francois Role
Summary: Biomedical scientific literature is growing rapidly, making it challenging to identify relevant results; automated information extraction tools based on text mining techniques are essential; deep neural networks have significantly advanced this research field.
BRIEFINGS IN BIOINFORMATICS
(2021)
Review
Biochemistry & Molecular Biology
Sofia I. R. Conceicao, Francisco M. Couto
Summary: In building biological networks, providing reliable interactions is crucial. Text mining methods can help extract knowledge from scientific literature to overcome the challenge of tracking recent discoveries. These tools can lead to more reliable and personalized networks by identifying relations between entities of interest.
Article
Biochemistry & Molecular Biology
Nicole Y. Souren, Norbert E. Fusenig, Stefanie Heck, Wilhelm G. Dirks, Amanda Capes-Davis, Franca Bianchini, Christoph Plass
Summary: Misidentification of cell lines is a serious threat to scientific reproducibility. Strict multi-layered quality control, collaborations between journals, research institutions, and funders, as well as regular authentication schemes and staff training, are essential to address this issue. Future steps should focus on enhancing good cell culture practices.
Review
Biochemistry & Molecular Biology
Ying Zhou, Hongyan Li, Hongzhe Sun
Summary: Metalloproteomics is an emerging interdisciplinary research field that investigates metal-protein interactions in biological systems at a proteome-wide scale. It has a positive impact on human health by increasing our understanding of metal homeostasis and the molecular mechanisms of action of metallodrugs. This review summarizes recent advances in methodologies and applications of metalloproteomics, and highlights the emerging field of single-cell metalloproteomics.
ANNUAL REVIEW OF BIOCHEMISTRY
(2022)
Article
Genetics & Heredity
Christopher Cherniak, Raul Rodriguez-Esteban
MOLECULAR CYTOGENETICS
(2019)
Article
Biochemical Research Methods
Raul Rodriguez-Esteban
Article
Biochemical Research Methods
Raul Rodriguez-Esteban
Summary: Through studying the relationship between annotations in biomedical articles and citation networks, it is found that an article's citation neighborhood plays a significant role in defining the annotated content of the article. This suggests that citations should be considered as a crucial foundation for future knowledge management and annotation of biomedical articles.
BMC BIOINFORMATICS
(2021)
Article
Computer Science, Information Systems
Raul Rodriguez-Esteban, Dina Vishnyakova, Fabio Rinaldi
Summary: Email is the primary method of communication with authors of scientific publications. This study found that about 18% of authors' contact email addresses in biomedical publications are invalid. The use of personal email addresses is increasing, and these addresses are found to be more reliable compared to other types of email addresses.
JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY
(2022)
Review
Pharmacology & Pharmacy
Ana Lucia Schmidt, Raul Rodriguez-Esteban, Juergen Gottowik, Mathias Leddin
Summary: This article reviews the latest developments in quantitative social media listening methods applied to drug discovery from the perspective of the pharmaceutical industry, discussing the need for patient-centric therapies and the importance of drawing from developments in artificial intelligence and real-world data analysis.
DRUG DISCOVERY TODAY
(2022)
Article
Neurosciences
Hannah Staunton, Kim Kelly, Louise Newton, Mathias Leddin, Raul Rodriguez-Esteban, K. Ray Chaudhuri, Daniel Weintraub, Ronald B. Postuma, Pablo Martinez-Martin
Summary: This study aims to create a conceptual model of symptoms and impacts for individuals with early-stage Parkinson's disease (PD) by collecting qualitative data. The results show that the most frequently reported symptoms in early-stage PD include tremors, stiffness and rigidity, and fatigue, while the most commonly reported impacts include anxiety, eating and drinking, and exercise/sport and relationship with family/family life. The conceptual model can be used to guide researchers in developing and selecting patient-centered outcomes for clinical trials and inform future qualitative research and outcome development specifically for early-stage PD patients.
JOURNAL OF PARKINSONS DISEASE
(2022)
Article
Multidisciplinary Sciences
Raul Rodriguez-Esteban
Summary: Delays in the propagation of scientific discoveries have been criticized for introducing bias and hindering scientific progress. This study quantitatively explores the negative impact on biomedical discovery and finds that the distance between scientific facts affects the probability of new discoveries. Opening the scope of scientific work with modern information retrieval methods is suggested as a solution.
Article
Medical Informatics
Tobe Che Benjamin Freeman, Raul Rodriguez-Esteban, Juergen Gottowik, Xing Yang, Veit Johannes Erpenbeck, Mathias Leddin
Summary: By analyzing a substantial corpus of social media content, insights into the patient experience of chronic obstructive pulmonary disease (COPD) were gained. The use of a neural network approach to identify a lexicon of community words and phrases specific to COPD symptoms deepened the understanding of the relationship between symptoms and disease impacts.
JMIR MEDICAL INFORMATICS
(2021)
Article
Medical Laboratory Technology
Raul Rodriguez-Esteban, Jose Duarte, Priscila C. Teixeira, Fabien Richard, Svetlana Koltsova, W. Venus So
Summary: The study found that machine learning methods can be used to predict annotations associated with gating definitions from flow cytometry assays. However, a hybrid automatic and manual annotation workflow is recommended for optimal results.
CYTOMETRY PART B-CLINICAL CYTOMETRY
(2022)
Article
Multidisciplinary Sciences
An Goto, Raul Rodriguez-Esteban, Sebastian H. Scharf, Garrett M. Morris
Summary: Drug resistance caused by mutations is a significant public health threat. This study provides a comprehensive perspective on Hepatitis B virus mutations by combining clinical research and genetic data from scientific literature, identifying mutational hotspots and a common mutation position related to anti-HBV drug binding.
SCIENTIFIC REPORTS
(2022)
Article
Mathematical & Computational Biology
Davy Weissenbacher, Karen O'Connor, Siddharth Rawal, Yu Zhang, Richard Tzong-Han Tsai, Timothy Miller, Dongfang Xu, Carol Anderson, Bo Liu, Qing Han, Jinfeng Zhang, Igor Kulev, Berkay Koprue, Raul Rodriguez-Esteban, Elif Ozkirimli, Ammer Ayach, Roland Roller, Stephen Piccolo, Peijin Han, V. G. Vinod Vydiswaran, Ramya Tekumalla, Juan M. Banda, Parsa Bagherzadeh, Sabine Bergler, Joao F. Silva, Tiago Almeida, Paloma Martinez, Renzo Rivera-Zavala, Chen-Kai Wang, Hong-Jie Dai, Luis Alberto Robles Hernandez, Graciela Gonzalez-Hernandez
Summary: This study presents the outcomes of BioCreative VII (Task 3) competition, which focused on extracting medication names from Twitter user's publicly available tweets. Detecting health-related tweets is challenging due to informal language and the vast majority of tweets unrelated to health. The task required addressing extreme class imbalance to find tweets mentioning medications. A total of 65 teams registered and 16 teams submitted systems. The study analyzed the corpus, methods, and results, with a focus on learning from class-imbalanced data.
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
(2023)
Review
Pharmacology & Pharmacy
Maria Bordukova, Nikita Makarov, Raul Rodriguez-Esteban, Fabian Schmich, Michael P. Menden
Summary: The concept of Digital Twins in drug development and clinical trials has the potential to advance precision medicine by improving efficiency and supporting biomarker discovery. Generative artificial intelligence plays a crucial role in creating realistic and complex data for Digital Twins.
EXPERT OPINION ON DRUG DISCOVERY
(2023)
Article
Mathematical & Computational Biology
Graciela Gonzalez-Hernandez, Martin Krallinger, Monica Munoz, Raul Rodriguez-Esteban, Ozlem Uzuner, Lynette Hirschman
Summary: Monitoring drug safety is a key concern, and stakeholders are interested in using text mining and AI methods to manage the increasing volume of information on toxicity and adverse events. BioCreative VII organized a panel of experts to explore challenges in mining drug adverse reactions, and this article is a result of their discussion. The highlighted applications showcase the opportunities and challenges for text mining in drug discovery, testing, marketing, and post-market surveillance. Stakeholders are eager to embrace natural language processing and AI tools, creating opportunities for collaboration with regulatory agencies, pharma, and the text mining community.
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
(2022)
Meeting Abstract
Critical Care Medicine
V. J. Erpenbeck, T. C. B. Freeman, R. Rodriguez-Esteban, J. Gottowik, M. Leddin
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE
(2020)
Article
Computer Science, Information Systems
Dina Vishnyakova, Raul Rodriguez-Esteban, Fabio Rinaldi
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
(2019)
