24 papers · ranked by Valyu relevance
Gabriel Rosenfeld, Dawei Lin
While the impact of biomedical research has traditionally been measured using bibliographic metrics such as citation or journal impact factor, the data itself is an output which can be directly measured to provide additional context about a publication’s impact. Data are a resource that can be repurposed and reused…
L Ohno-Machado, SA Sansone, G Alter, I Fore + 7 more
The value of broadening searches for data across multiple repositories has been identified by the biomedical research community. As part of the NIH Big Data to Knowledge initiative, we work with an international community of researchers, service providers and knowledge experts to develop and test a data index and…
Mingrui Liu, Zelin Ye, Haiyu Liu, Pengzhen Ma + 6 more
This review provides a representative overview of public biomedical databases and their use in biomedical research. These resources are categorized into four major types according to their dominant data content: public health databases, clinical databases, comprehensive cohort databases, and omics databases. For each…
Heming Zhang, Shunning Liang, Tim Xu, Wenyu Li + 15 more
Artificial intelligence (AI) is revolutionizing scientific discovery because of its super capability, following the neural scaling laws, to integrate and analyze large-scale datasets to mine knowledge. Foundation models, large language models (LLMs) and large vision models (LVMs), are among the most important…
Alejandro Lozano, Min Woo Sun, James Burgess, Jeffrey J. Nirschl + 15 more
'Christopher Polzak' 'Yuhui Zhang' 'Liangyu Chen' 'Jeffrey Gu' 'Ivan Lopez' 'Josiah Aklilu' 'Anita Rau' 'Austin Wolfgang Katzer' 'Collin Chiu' 'Orr Zohar' 'Xiaohan Wang' 'Alfred Seunghoon Song' 'Chiang Chia-Chun' 'Robert Tibshirani' 'Serena Yeung-Levy'] | Alejandro Lozano1 | | Min Woo Sun1 James Burgess*1 | Jeffrey J.…
Yovaninna Alarcón‐Soto, Jenifer Espasandín-Domínguez, Ipek Guler, Mercedes Conde‐Amboage + 4 more
'Mercedes Conde‐Amboage' 'Francisco Gudé' 'Klaus Langohr' 'Carmén Cadarso-Suárez' 'Guadalupe Gómez Melis'] Abstract: We highlight the role of Data Science in Biomedicine. Our manuscript goes from the general to the particular, presenting a global definition of Data Science and showing the trend for this discipline…
Susanna-Assunta Sansone, Alejandra Gonzalez-Beltran, Philippe Rocca-Serra, George Alter + 12 more
Today’s science increasingly requires effective ways to find and access existing datasets that are distributed across a range of repositories. For researchers in the life sciences, discoverability of datasets may soon become as essential as identifying the latest publications via PubMed. Through an international…
Wilson Wen Bin Goh, Limsoon Wong
Biology is becoming increasingly digitized and has now taken on the sheen of a quantitative scientific discipline. A key driving factor is the increasing pervasiveness of high-throughput technological platforms in biological research, allowing millions of data points on genes, proteins, and other biological moieties…
Michelle C. Dunn, Philip E. Bourne
This article describes efforts at the National Institutes of Health (NIH) from 2013 to 2016 to train a national workforce in biomedical data science. We provide an analysis of the Big Data to Knowledge (BD2K) training program strengths and weaknesses with an eye toward future directions aimed at any funder and…
Indra Neil Sarkar
Biomedical Informatics is a transdisciplinary discipline that spans the full range of biomedical applications. There are foundational methodologies that transcend these application areas, which are the basis for functional subgroups of biomedical informatics. Examples of these subgroups include Translational…
Oscar Mora, Jesús Bisbal
In this paper, we present BIMS (Biomedical Information Management System). BIMS is a software architecture designed to provide a flexible computational framework to manage the information needs of a wide range of biomedical research projects. The main goal is to facilitate the clinicians' job in data entry, and…
Daniall Masood, Mariia Kim, Jeet Vora, Robel Kahsay + 26 more
Biomarkers are essential tools for disease detection, risk assessment, therapeutic monitoring, and precision medicine. However, biomarker data are dispersed across heterogeneous resources, inconsistently reported in the literature, and rarely standardized for computational use. This fragmentation limits…
Christine L. Borgman, Philip E. Bourne
| 1 | Introduction | 2 | 2 | Individual | Scientists | as | Stakeholders | 3 | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 3 | Academic | Institutional | Stakeholders | | 4 | 3.1 | Academic | Leadership | 5 | | | | 3.2 | Research | Computing 5 | 3.3 | University | Libraries | 6 | |…
Anna C. Greene, Kristine A. Giffin, Casey S. Greene, Jason H. Moore
Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of…
Jason H. Moore, John H. Holmes
Biomedical informatics has become a central focus for many academic medical centers and universities as biomedical research because increasingly reliant on the processing, analysis, and interpretation of large volumes of data, information, and knowledge. We posit here that this is the beginning of the golden era of…
Authors not listed
Artificial intelligence (AI) is reshaping scientific research by accelerating discovery and enabling the analysis of complex data that traditional methods struggle to handle. This review examines over 310,000 journal articles and patents from the CAS Content Collection (2015–2025), with a focus on, biomedical research…
O. P. Trifonova, V. A. Il’in, E. V. Kolker, A. V. Lisitsa
FORUM The task of extracting new knowledge from large data sets is designated by the term “Big Data.” To put it simply, the Big Data phenomenon is when the results of your experiments cannot be imported into an Excel file. Estimated, the volume of Twitter chats throughout a year is several orders of magnitude larger…
Deepak Unni, Sierra Moxon, Michael Bada, Matthew Brush + 20 more
'Richard Bruskiewich' 'Paul A. Clemons' 'Vlado Dančík' 'Michel Dumontier' 'Karamarie Fecho' 'Gustavo Glusman' 'Jennifer Hadlock' 'Nomi L. Harris' 'Arpita Joshi' 'Tim Putman' 'Guangrong Qin' 'Stephen A. Ramsey' 'Kent Shefchek' 'Harold R. Solbrig' 'Karthik Soman' 'Anne Thessen' 'Melissa Haendel' 'Chris Bizon' 'Chris…
Tiqing Liu, Linda Hwang, Stephen K Burley, Carmen I Nitsche + 3 more
BindingDB (bindingdb.org) is a public, web-accessible database of experimentally measured binding affinities between small molecules and proteins, which supports diverse applications including medicinal chemistry, biochemical pathway annotation, training of artificial intelligence models, and computational chemistry…
Long Qian, Xin Lu, Parvez Haris, Jianyong Zhu + 2 more
Clinical trials are crucial for drug development, but they require significant time and financial resources. Additionally, uncertainties may arise during these trials concerning their results due to concerns surrounding effectiveness, safety, or the enrollment of participants. If robust AI (artificial intelligence)…
Michael C. Schatz
The last 20 years have been a remarkable era for biology and medicine. One of the most significant achievements has been the sequencing of the first human genomes, which has laid the foundation for profound insights into human genetics, the intricacies of regulation and development, and the forces of evolution.…
Chia-Wei Hsu, Terra Williams, Xiang Yu
3D printing has been applied to multiple areas since 1980. Biomedical applications have grown significantly and become the mainstream of 3D printing applications. In this review, we elucidated the publication distribution of biomedical 3D printing using the CAS Content Collection. From 2010 to 2021, journal and patent…
Jan Range, Colin Halupczok, Jens Lohmann, Neil Swainston + 6 more
EnzymeML is an XML–based data exchange format that supports the comprehensive documentation of enzymatic data by describing reaction conditions, time courses of substrate and product concentrations, the kinetic model, and the estimated kinetic constants. EnzymeML is based on the Systems Biology Markup Language, which…
Rebecca Brunk, Kriti Shukla, Bryant Hutson, Yue Wang + 7 more
Genomic sequencing and other big biological data is unquestionably of paramount value, however the success in recruiting highly skilled individuals with diverse backgrounds has been limited. A main reason for this deficiency could be due to the lack of educational resources and early exposure to the field. With the…