Python - All a Scientist Needs

@misc{citeulike:2671108, abstract = {Any cutting-edge scientific research project requires a myriad of computational tools for data generation, management, analysis and visualization. Python is a flexible and extensible scientific programming platform that offered the perfect solution in our recent comparative genomics investigation (J. B. Lucks, D. R. Nelson, G. Kudla, J. B. Plotkin. Genome landscapes and bacteriophage codon usage, PLoS Computational Biology, 4, 1000001, 2008). In this paper, we discuss the challenges of this project, and how the combined power of Biopython, Matplotlib and SWIG were utilized for the required computational tasks. We finish by discussing how python goes beyond being a convenient programming language, and promotes good scientific practice by enabling clean code, integration with professional programming techniques such as unit testing, and strong data provenance.}, author = {Lucks, Julius B. }, citeulike-article-id = {2671108}, eprint = {0803.1838}, keywords = {arxiv, bioinformatics, programming, python}, month = {Mar}, posted-at = {2008-04-15 03:31:52}, priority = {2}, title = {Python - All a Scientist Needs}, url = {http://arxiv.org/abs/0803.1838}, year = {2008} }

TY - ELEC ID - citeulike:2671108 L3 - citeulike-article-id:2671108 TI - Python - All a Scientist Needs N2 - Any cutting-edge scientific research project requires a myriad of computational tools for data generation, management, analysis and visualization. Python is a flexible and extensible scientific programming platform that offered the perfect solution in our recent comparative genomics investigation (J. B. Lucks, D. R. Nelson, G. Kudla, J. B. Plotkin. Genome landscapes and bacteriophage codon usage, PLoS Computational Biology, 4, 1000001, 2008). In this paper, we discuss the challenges of this project, and how the combined power of Biopython, Matplotlib and SWIG were utilized for the required computational tasks. We finish by discussing how python goes beyond being a convenient programming language, and promotes good scientific practice by enabling clean code, integration with professional programming techniques such as unit testing, and strong data provenance. KW - arxiv KW - bioinformatics KW - programming KW - python AU - Lucks, Julius PY - 2008/Mar/12/ UR - http://arxiv.org/abs/0803.1838 ER -