Chemotaxis Pathways

Deciphering Chemotaxis Pathways Using Cross Species Comparisons

Predicting gene clusters - a statistical method based on the Corrected Akaike Information Criterion (AICC)

1. data (txt: [all.genes.parB.slp.locations2])
2. program (Python scripts: [Partition.genes.py], [Clustering_by_AIC.py])
3. predicted gene clusters (txt: [Clusters.[AICC].[all.genes.parB.slp.locations2].txt])

Storing gene clusters in Python shelve format

1. programs (Python scripts: [ABRWY], [ABRW])
2. python shelves (Python library shelves: [ABRWY], [ABRW])

Calculating the observed clustering of our operons

1. programs (Python scripts, [ABRWY], [ABRW])
2. python shelves (Python library shelves, [ABRWY], [ABRW])

Predicting chemotaxis pathways

1. input datasets (gene clusters, observed clustering of the gene clusters, in python shelve format)
2. programs for chemotaxis models (Zipped Python scripts, [ABRWY], [ABRW+Y], [ABRWY+Y], [ABRWY+Y])
3. predicted pathways

Miscelaneous

1. additional perl scripts