. "B Challenge Problems in Bioinformatics and Computational Biology from Other Reports." Catalyzing Inquiry at the Interface of Computing and Biology. Washington, DC: The National Academies Press, 2005.
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Catalyzing Inquiry at the Interface of Computing and Biology
Complete construction of orthologous and paralogous groups of genes
Structure determination of large macromolecular assemblies/complexes
Dynamical simulation of realistic oligomeric systems
Rapid structural/topological clustering of proteins
Prediction of unknown molecular structures; protein folding
Computer simulation of membrane structure and dynamic function
Simulation of genetic networks and the sensitivity of these pathways to component stoichiometry and kinetics
Integration of observations across scales of vastly different dimensions and organization to yield realistic environmental models for basic biology and societal needs
B.5TECHNOLOGIES FOR BIOLOGICAL COMPUTER-AIDED DESIGN (Masaru Tomita)5
Enzyme engineering: to refine enzymes and to analyze kinetic parameters in vitro
Metabolic engineering: to analyze flux rates in vivo
Analytical chemistry: to determine and analyze the quantity of metabolites efficiently
Genetic engineering: to cut and paste genes on demand, for modifying metabolic pathways
Simulation science: to efficiently and accurately simulate a large number of reactions
Knowledge engineering: to construct, edit and maintain large metabolic knowledge bases
Mathematical engineering: to estimate and tune unknown parameters
B.6TOP BIOINFORMATICS CHALLENGES (Chris Burge et al.)6
Precise, predictive model of transcription initiation and termination: ability to predict where and when transcription will occur in a genome
Precise, predictive model of RNA splicing/alternative splicing: ability to predict the splicing pattern of any primary transcript
Precise, quantitative models of signal transduction pathways:ability to predict cellular response to external stimuli
Determining effective protein-DNA, protein-RNA and protein-protein recognition codes
Accurate ab initio structure prediction
Rational design of small molecule inhibitors of proteins
Mechanistic understanding of protein evolution: understanding exactly how new protein functions evolve
Mechanistic understanding of speciation: molecular details of how speciation occurs
Continued development of effective gene ontologies-systematic ways to describe the functions of any gene or protein
(Infrastructure and education challenge)
Education: development of appropriate bioinformatics curricula for secondary, undergraduate, and graduate education
B.7EMERGING FIELDS IN BIOINFORMATICS (Patricia Babbitt)7
Data storage and retrieval, database structures, annotation
Analysis of genomic/proteomic/other high-throughput information
5
M. Tomita, “Towards Computer Aided Design (CAD) of Useful Microorganisms,” Bioinformatics 17(12):1091-1092, 2001.
