The Abstracts track is a perfect place for bioinformatics researchers and medical informaticians to introduce their preliminary research outcomes to increase research impact and to nurture collaborations. We emphasize research effectiveness on real-world datasets. Submitted abstracts will be peer-reviewed by the program committee to make sure that the content would be of interest to the KDD audience including researchers, practitioners and trainees, and authors of accepted abstracts will be asked to give a poster presentation, with quality ones invited for a 5-minute spotlight presentation. We invite the submission of abstracts about research contributions in (but not limited to) the following two broad areas (and their subareas):
Area 1: Knowledge Discovery from Clinical Data
- Extracting risk factors/symptoms of diseases form EHRs (electronic health records)
- Generating lexicons/vocabularies of diseases of interest
- Longitudinal analysis of temporal data in EHRs
- EHR content summarization
- Topic modeling of clinical text data
- Pharmacogenomics and adverse events mining from EHR data
- Multi-view learning of heterogeneous EHR data
- Decision support tools for big EHR data
- Visualization techniques to facilitate query and analysis of clinical data
- Mining medical images
- Privacy and security issues in mining genomic databases and EHR
Area 2: Knowledge Discovery from Biological Data
- Structural bioinformatics
- Discovering biological networks and pathways underlying biological processes and diseases
- Analysis, discovery of biomarkers and mutations, and disease risk assessment
- Comparative genomics
- Metagenome analysis using sequencing data
- RNA-seq and microarray-based gene expression analysis
- Genome-wide analysis of non-coding RNAs
- Genome-wide regulatory motif discovery
- Automated annotation of genes and proteins
- Discovery of structural variations from next-generation sequencing (NGS) data
- Discovery of genotype-phenotype associations
- Building predictive models for complex phenotypes
- Semantic web and ontology-driven data integration methods
Submission Guidelines
Abstracts should be at most 1 page in length, single-spaced, in font size 10 or larger with one-inch margins on all sides. Using the ACM Proceedings Format is highly recommended. An abstract should be submitted in PDF format through EasyChair at the following link: https://easychair.org/conferences/?conf=biokdd2018.