We have introduced a standalone, Perl-based pipeline for protein structure prediction that integrates freely downloadable software components from various academic and government research laboratories.
Integrating freely-available environment-gene interaction and disease phenotype data would allow hypothesis generation for potential environmental associations to disease.
Such approaches are integrated and freely available in the open source Python software package BooleanNet[ 19] or in the R[ 20] package BoolNet[ 21], for example.
The latter integrates freely available depth and thickness information from wells and seismic lines and has been additionally constrained by 3D gravity modelling.
Moreover, the model integrates all freely available depth and thickness information (wells, seismic lines) as well as faults as interpolation barriers and has been additionally constrained by 3D gravity modelling.
Even though people appreciate natural complexity, which allows them to select and integrate information freely, they have difficulties in handling formalised complexity, which requires particular kinds of experience and logic.
Modular molecular information processing can often be achieved through protein assemblies, which serve to integrate otherwise freely diffusible signals and is amenable to facile evolution and synthetic reengineering.
The clusters obtained by assembling EST sequences from GenBank and our ESTs were mined for SNPs using a pipeline that integrates six freely available SNP discovery tools: SNPserver [ 48], PolyBayes [ 49], Quality SNP [ 50], PolyFreq [ 51], MiraEST [ 52], and ssahaSNP [ 53].
The software is integrated into a freely available web service at http://met-hilab.cbs.dtu.dk/blockcons/.
