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The International Conference on Intelligent Biology and Medicine (ICIBM) 2020: Scalable techniques and algorithms for computational genomics
- Source :
- BMC Genomics, Vol 21, Iss S11, Pp 1-5 (2020), BMC Genomics
- Publication Year :
- 2020
- Publisher :
- BMC, 2020.
-
Abstract
- In this introduction article, we summarize the 2020 International Conference on Intelligent Biology and Medicine (ICIBM 2020) conference which was held on August 9–10, 2020 (virtual conference). We then briefly describe the nine research articles included in this supplement issue. ICIBM 2020 hosted four scientific sections covering current topics in bioinformatics, computational biology, genomics, biomedical informatics, among others. A total of 75 original manuscripts were submitted to ICIBM 2020. All the papers were under rigorous review (at least three reviewers), and highly ranked manuscripts were selected for oral presentation and supplement issues. This genomics supplement issue included nine manuscripts. These articles cover methods and applications for single cell RNA sequencing, multi-omics data integration for gene regulation, gene fusion detection from long-read RNA sequencing, gene co-expression analysis of metabolic pathways in cancer, integrative genome-wide association studies (GWAS) of subcortical imaging phenotype in Alzheimer’s disease, as well as deep learning methods for protein structure prediction, metabolic pathway membership inference, and horizontal gene transfer (HGT) insertion sites prediction.
- Subjects :
- lcsh:QH426-470
lcsh:Biotechnology
MEDLINE
Genome-wide association study
Genomics
Computational biology
Biology
computer.software_genre
Proteomics
Health informatics
lcsh:TP248.13-248.65
Genetics
Introduction
business.industry
Computational genomics
Computational Biology
lcsh:Genetics
Scalability
Medicine
business
computer
Algorithms
Biotechnology
Data integration
Genome-Wide Association Study
Subjects
Details
- Language :
- English
- ISSN :
- 14712164
- Volume :
- 21
- Database :
- OpenAIRE
- Journal :
- BMC Genomics
- Accession number :
- edsair.doi.dedup.....f3ef4110b68bec3a66c3e5a509f85edf