BioData Mining (Record no. 3401)
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| fixed length control field | 03697nas a22003495i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 1756-0381 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260610082518.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 150723s||||||||xxkuu poo|||||| b|EN |d |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER | |
| International Standard Serial Number | 1756-0381 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 13040 |
| Source of number or code | local |
| 210 10 - ABBREVIATED TITLE | |
| Abbreviated title | BioData Mining |
| 245 10 - TITLE STATEMENT | |
| Title | BioData Mining |
| Medium | [electronic resource] / |
| Statement of responsibility, etc. | edited by Jason Moore, Marylyn Ritchie, Nicholas Tatonetti. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | London : |
| Name of producer, publisher, distributor, manufacturer | BioMed Central : |
| -- | Imprint: BioMed Central. |
| 300 ## - online resource | |
| Other physical details | online resource. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | BioData Mining is an open access, open peer-reviewed informatics journal publishing rigorous and creative computational research at the interface of Artificial Intelligence, Machine Learning, biomedical data science, and translational informatics. The journal focuses on methodological, computational, and informatics contributions that advance how complex biological and biomedical data are represented, modeled, integrated, evaluated, interpreted, and translated into scientific or clinical insight. BioData Mining welcomes work in biology, medicine, and basic science when the computational contribution is central and broadly useful beyond a single dataset, disease, cohort, or assay. The journal prioritizes studies that introduce, adapt, evaluate, or creatively apply AI and data mining methods to high-dimensional biomedical data, especially when they demonstrate methodological rigor, thoughtful data representation, meaningful validation, interpretability, and potential for generalization. Topical areas include, but are not limited to: Development, evaluation, and application of novel machine learning, artificial intelligence, statistical, and data mining methods. Rigorous adaptation and evaluation of existing computational methods when applied in a biologically or clinically meaningful and methodologically insightful way. Foundation models, representation learning, probing, adapter methods, retrieval-augmented systems, and agentic AI approaches for biomedical discovery and translational informatics. Multimodal, longitudinal, temporal, and real-world biomedical data modeling, including approaches that address missingness, bias, confounding, calibration, uncertainty, robustness, data drift, and external validation. Open-source software, benchmarks, datasets, databases, and web services that support reproducible, reusable, and generalizable biomedical AI and data mining research. Pre-processing, post-processing, interpretation, visualization, and evaluation frameworks that improve knowledge discovery from complex biomedical data. Data types include: Imaging Electronic health records Claims and administrative data Biobanks Genomic, transcriptomic, proteomic, metabolomic, and other omics data Environmental exposure data Social determinants of health Social and behavioral data Wearable and sensor data Patient-generated data Biomedical literature, knowledge graphs, and other structured or unstructured knowledge sources. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Bioinformatics. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Bioinformatics. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Algorithms. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Computational and Systems Biology. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Data Mining and Knowledge Discovery. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Bioinformatics. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Algorithms. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Moore, Jason. |
| Relator term | editor. |
| Relationship | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Ritchie, Marylyn. |
| Relator term | editor. |
| Relationship | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Tatonetti, Nicholas. |
| Relator term | editor. |
| Relationship | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://biodatamining.biomedcentral.com/">https://biodatamining.biomedcentral.com/</a> |
| Public note | Open Access |
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