title: A statistical physics perspective on alignment-independent protein sequence comparison.
abstract: BACKGROUND
  Within bioinformatics, the textual alignment of amino acid sequences has long dominated the determination of similarity between proteins, with all that implies for shared structure, function and evolutionary descent. Despite the relative success of modern-day sequence alignment algorithms, so-called alignment-free approaches offer a complementary means of determining and expressing similarity, with potential benefits in certain key applications, such as regression analysis of protein structure-function studies, where alignment-base similarity has performed poorly.
  
  
  RESULTS
  Here, we offer a fresh, statistical physics-based perspective focusing on the question of alignment-free comparison, in the process adapting results from 'first passage probability distribution' to summarize statistics of ensemble averaged amino acid propensity values. In this article, we introduce and elaborate this approach.
authors: School of Engineering and Applied Science, Nonlinearity and Complexity Research Group and.
authors: Amit K
authors: AK
authors: Chattopadhyay
authors: School of Engineering and Applied Science, Nonlinearity and Complexity Research Group and.
authors: Diar
authors: D
authors: Nasiev
authors: School of Life and Health Sciences, University of Aston, Aston Triangle, Birmingham, UK.
authors: Darren R
authors: DR
authors: Flower
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D010825:Physics; D016415:Sequence Alignment; D020539:Sequence Analysis, Protein / Q000379:methods*