Using the P ython programming language for bioinformatics
- 15 April 2005
- book chapter
- Published by Wiley
Abstract
Molecular biology is evolving from the study of macromolecules in isolation toward complex environments, potentially as large as complete cells. The amount and heterogeneity of information that needs to be processed and integrated in order to understand and simulate such complexity requires a leap in the level of sophistication of our software tools. In this article, we describe the advantages of interpretive languages in general and Python in particular, over compiled languages for tackling this formidable software engineering and integration problem.Keywords
This publication has 5 references indexed in Scilit:
- Computer-linked autofabricated 3D models for teaching structural biologyPublished by Association for Computing Machinery (ACM) ,2004
- PHENIX: building new software for automated crystallographic structure determinationActa Crystallographica Section D-Biological Crystallography, 2002
- Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy functionJournal of Computational Chemistry, 1998
- VMD: Visual molecular dynamicsJournal of Molecular Graphics, 1996
- WHAT IF: A molecular modeling and drug design programJournal of Molecular Graphics, 1990