Title |
PyElph - a software tool for gel images analysis and phylogenetics
|
---|---|
Published in |
BMC Bioinformatics, January 2012
|
DOI | 10.1186/1471-2105-13-9 |
Pubmed ID | |
Authors |
Ana Brânduşa Pavel, Cristian Ioan Vasile |
Abstract |
This paper presents PyElph, a software tool which automatically extracts data from gel images, computes the molecular weights of the analyzed molecules or fragments, compares DNA patterns which result from experiments with molecular genetic markers and, also, generates phylogenetic trees computed by five clustering methods, using the information extracted from the analyzed gel image. The software can be successfully used for population genetics, phylogenetics, taxonomic studies and other applications which require gel image analysis. Researchers and students working in molecular biology and genetics would benefit greatly from the proposed software because it is free, open source, easy to use, has a friendly Graphical User Interface and does not depend on specific image acquisition devices like other commercial programs with similar functionalities do. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Japan | 2 | 25% |
Germany | 1 | 13% |
Venezuela, Bolivarian Republic of | 1 | 13% |
United Kingdom | 1 | 13% |
Unknown | 3 | 38% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 63% |
Scientists | 3 | 38% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | <1% |
Brazil | 2 | <1% |
South Africa | 2 | <1% |
Germany | 1 | <1% |
Indonesia | 1 | <1% |
Uganda | 1 | <1% |
Colombia | 1 | <1% |
India | 1 | <1% |
Czechia | 1 | <1% |
Other | 6 | 2% |
Unknown | 332 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 68 | 19% |
Researcher | 55 | 16% |
Student > Master | 44 | 13% |
Student > Bachelor | 41 | 12% |
Student > Doctoral Student | 19 | 5% |
Other | 63 | 18% |
Unknown | 61 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 143 | 41% |
Biochemistry, Genetics and Molecular Biology | 59 | 17% |
Immunology and Microbiology | 24 | 7% |
Environmental Science | 17 | 5% |
Engineering | 8 | 2% |
Other | 25 | 7% |
Unknown | 75 | 21% |