BIO 2012 - ACM-SAC 2012 CONFERENCE TRACK ON BIOINFORMATICS AND COMPUTATIONAL SYSTEMS BIOLOGY (BIO)

For the past twenty-six years, the ACM Symposium on Applied Computing has been a primary gathering forum for applied computer scientists, computer engineers, software engineers, and application developers from around the world. SAC 2012 is sponsored by the ACM Special Interest Group on Applied Computing (SIGAPP), and is hosted by COSBI at Riva del Garda Congress Center, Italy.
TRACK DESCRIPTION

The track aims at proposing a multi-sides perspective to computational biology, bioinformatics and theoretical systems biology. All these three areas involve the development and application of analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological sciences. Currently, the field of application of mathematical and computer science investigation methods to the life sciences is not limited to theoretical modeling in biochemistry, molecular biology and epidemiological biomathematics. Now bioinformatics and computational biology extend also to larger scale systems like ecological systems and include more applicative fields such as pharmacology, medicine, clinical trials design, healthcare and environment. Three ad-hoc topics are added to the more traditional topics of Bio-Track of ACM. These topics are: (i) stochastic ecosystem models, (ii) parallel interacting processes in ecology and (iii) hierarchical modeling at several organizational levels (show/hide more details).
CONFERENCE TRACK TOPICS

Papers are solicited in, but not limited to the following areas:

Algebraic Biology
Bio-ontologies
Bioinformatics for diseases
Biological data quality and data cleaning
Biological data sharing and update propagation
Biological metadata management
Comparative genomics
Computational genomics
Computational systems biology
(show/hide more topics)
Data visualization and visual analytics
Databases and data Integration
Databases and ontologies
DNA assembly, clustering and mapping
Drug design
Drug targeting
Errors and inconsistencies in biological databases
Evolution and phylogenetics
Gene expression and regulation from microarray data
Gene identification and annotation
Gene networks
Genomes and protein analysis
High-performance bio-computing
In silico clinical trials
Integrative approaches for drug design
Biological network inference
Integrative data and text mining approaches
Laboratory information management systems in biology
Machine learning and data integration in life sciences
Mining integrated life sciences data
Model driven analysis of biological systems
Molecular databases and data warehouses
Molecular modeling and simulation
Molecular sequence analysis
Network analysis
Parallel architectures and algorithms for biological applications
Pathways, networks, systems biology
Pattern discovery and classification
Pharmacokinetics/pharmacodynamics modeling
Phylogeny reconstruction algorithms
Population genetics
Prediction and integration of metabolic and regulatory networks
Protein, RNA and DNA structure and function
Protein interactions and molecular networks
Protein structure prediction and modeling
Protein-protein interactions
Proteomics
Quality and consistency of biological ontologies
Query processing and optimization for biological data
Recognition of genes and regulatory elements
RNA and protein structure prediction
Semantic web for the life sciences
Sequence analysis and alignment
Sequence assembly
SNPs and haplotyping
Stochastic ecosystem models
Parallel and interacting processes in ecology
Hierarchical modeling at several organizational levels
Structural and functional genomics
Structural bioinformatics
System biology and modeling
System prototypes for biology
Text mining
Therapeutic targets discovery
Tool integration and workflow systems
Transcriptomics
Virtual cell