BioData Mining
BioData Mining is a peer-reviewed open access scientific journal covering data mining methods applied to computational biology published by BioMed Central.[1] It was established in 2008.[2]
 | |
| Discipline | data mining, bioinformatics, machine learning, computational biology |
|---|---|
| Language | English |
| Edited by | Jason H. Moore, Marylyn D. Ritchie |
| Publication details | |
| History | 2008–present |
| Publisher | |
| yes | |
| 2.672 (2019) | |
| Standard abbreviations | |
| ISO 4 | BioData Min. |
| Indexing | |
| CODEN | BMIIAP |
| ISSN | 1756-0381 |
| LCCN | 2009243015 |
| OCLC no. | 239727180 |
| Links | |
Its current impact factor is 2.672.[3]
Abstracting and indexing
The journal is abstracted and indexed by:
- Biological Abstracts
- BIOSIS
- Chemical Abstracts Service
- Embase
- EmBiology
- EmCare
- MEDLINE/PubMed
- Science Citation Index Expanded
- Scopus
gollark: For example: a 3D printer will let you make random plastic parts cheaply, *but* it needs microprocessors to work, and silicon fabs are literally the most capital intensive industry.
gollark: Although it also creates horribly difficult manufacturing processes.
gollark: Advancing technology allows more local production somewhat.
gollark: osmarks.net will consider your connection a lost cause after 5 seconds.
gollark: The problems are similar to ones people are already solving *now*, for distributed systems with offline mode.
External links
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