TrackSig is a method to estimate the evolutionary trajectories of signatures of somatic mutational processes. TrackSig uses cancer cell fraction (CCF) corrected by copy number to infer an approximate order in which the somatic mutations accumulate. TrackSig segments mutation ordering by CCF and fits signature exposures (activities) as a piece-wise constant function of the mutation ordering. TrackSig uses optimal segmentation to find the points of change in signature activities.
Cancer3D database provides an open and user-friendly way to analyze cancer missense mutations in the context of structures of proteins they are found in and in relation to patients gender and age.
HotSpot3D can be used to identify the mutation hotspots in the linear 1D sequence and correlates these hotspots with known or potential interacting domains based on both known intermolecular interactions and calculated proximity for potential intramolecular interactions.
RNAmutants is a web server to perform mutational analysis for a given RNA sequence. Previous methods relied on exhaustively enumerating k-point mutant sequences and subsequently applying mfold or RNAfold, a procedure with run time exponential in k. In contrast, RNAmutants computes the minimum free energy structure and Boltzmann partition function for all k-point mutants, for 0 ≤ k ≤ K, with run time O(K2n3).
The CMAT is a fully automated and reliable web-server for correlated mutation analysis. CMAT automatically performs all the processes for correlated mutation analysis including homology search, multiple sequence alignment construction, sequence redundancy treatment, and various correlated mutation score measures.
CanPredict uses a combination of computational methods to identify those changes most likely to be cancer-associated. Paste your sequence and change(s) below to generate a prediction.