Publication Date:
2015-08-07
Description:
A novel approach to Contact Map Overlap (CMO) problem is proposed using the two dimensional clusters present in the contact maps. Each protein is represented as a set of the non-trivial clusters of contacts extracted from its contact map. The approach involves finding matching regions between the two contact maps using approximate 2D-pattern matching algorithm and dynamic programming technique. These matched pairs of small contact maps are submitted in parallel to a fast heuristic CMO algorithm. The approach facilitates parallelization at this level since all the pairs of contact maps can be submitted to the algorithm in parallel. Then, a merge algorithm is used in order to obtain the overall alignment. As a proof of concept, MSVNS, a heuristic CMO algorithm is used for global as well as local alignment. The divide and conquer approach is evaluated for two benchmark data sets that of Skolnick and Ding et al. It is interesting to note that along with achieving saving of time, better overlap is also obtained for certain protein folds.
Print ISSN:
1545-5963
Electronic ISSN:
1557-9964
Topics:
Biology
,
Computer Science
Published by
Institute of Electrical and Electronics Engineers (IEEE)
on behalf of
The IEEE Computational Intelligence Society ; The IEEE Computer Society ; The IEEE Control Systems Society ; The IEEE Engineering in Medicine and Biology Society ; The Association for Computing Machinery.
