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This chapter discusses the various computational models of the brain to study brain functions.
In this context worst case analysis as well as many experimental studies were performed for various computational models.
This work relies mostly on simulation results obtained with the use of various computational models that are described.
To date, various computational models have been proposed to mimic the hierarchical processing of the ventral visual pathway, with limited success.
There are various computational models for V1 that seek to explain its visual functions in terms of its architecture and connections.
For this reason, assembling a pair of haplotypes from individual SNP fragments drives research and generates various computational models for this problem.
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Several computational models exist that attempt to explain and reproduce the experimentally observed segregation processes in various systems.
These results improve on previously known algorithms developed on various parallel computational models.
In this chapter, we present a brief overview of bioinformatics data sources and tools for system biologists, and the various computational and statistical models developed for a comprehensive understanding of cellular regulatory network.
Various statistical and computational models have been developed to characterize binding affinity [ 10, 11].
Participants of the DREAM4 challenge developed various computational approaches to model the signaling network and predict their cellular responses to different stimuli.
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