Quantiprot - a Python package for quantitative analysis of protein sequences
Abstract Background The field of protein sequence analysis is dominated by tools rooted in substitution matrices and alignments. A complementary approach is provided by methods of quantitative characterization. A major advantage of the approach is that quantitative properties defines a multidimensio...
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| Format: | Article |
| Language: | English |
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BMC
2017-07-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-017-1751-4 |
| _version_ | 1811322527514886144 |
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| author | Bogumił M. Konopka Marta Marciniak Witold Dyrka |
| author_facet | Bogumił M. Konopka Marta Marciniak Witold Dyrka |
| author_sort | Bogumił M. Konopka |
| collection | DOAJ |
| description | Abstract Background The field of protein sequence analysis is dominated by tools rooted in substitution matrices and alignments. A complementary approach is provided by methods of quantitative characterization. A major advantage of the approach is that quantitative properties defines a multidimensional solution space, where sequences can be related to each other and differences can be meaningfully interpreted. Results Quantiprot is a software package in Python, which provides a simple and consistent interface to multiple methods for quantitative characterization of protein sequences. The package can be used to calculate dozens of characteristics directly from sequences or using physico-chemical properties of amino acids. Besides basic measures, Quantiprot performs quantitative analysis of recurrence and determinism in the sequence, calculates distribution of n-grams and computes the Zipf’s law coefficient. Conclusions We propose three main fields of application of the Quantiprot package. First, quantitative characteristics can be used in alignment-free similarity searches, and in clustering of large and/or divergent sequence sets. Second, a feature space defined by quantitative properties can be used in comparative studies of protein families and organisms. Third, the feature space can be used for evaluating generative models, where large number of sequences generated by the model can be compared to actually observed sequences. |
| first_indexed | 2024-04-13T13:36:38Z |
| format | Article |
| id | doaj.art-28deb87f318d41669d3292eb7338e004 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-04-13T13:36:38Z |
| publishDate | 2017-07-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-28deb87f318d41669d3292eb7338e0042022-12-22T02:44:45ZengBMCBMC Bioinformatics1471-21052017-07-011811610.1186/s12859-017-1751-4Quantiprot - a Python package for quantitative analysis of protein sequencesBogumił M. Konopka0Marta Marciniak1Witold Dyrka2Katedra InŻynierii Biomedycznej, Wydział Podstawowych Problemów Techniki, Politechnika WrocławskaKatedra InŻynierii Biomedycznej, Wydział Podstawowych Problemów Techniki, Politechnika WrocławskaKatedra InŻynierii Biomedycznej, Wydział Podstawowych Problemów Techniki, Politechnika WrocławskaAbstract Background The field of protein sequence analysis is dominated by tools rooted in substitution matrices and alignments. A complementary approach is provided by methods of quantitative characterization. A major advantage of the approach is that quantitative properties defines a multidimensional solution space, where sequences can be related to each other and differences can be meaningfully interpreted. Results Quantiprot is a software package in Python, which provides a simple and consistent interface to multiple methods for quantitative characterization of protein sequences. The package can be used to calculate dozens of characteristics directly from sequences or using physico-chemical properties of amino acids. Besides basic measures, Quantiprot performs quantitative analysis of recurrence and determinism in the sequence, calculates distribution of n-grams and computes the Zipf’s law coefficient. Conclusions We propose three main fields of application of the Quantiprot package. First, quantitative characteristics can be used in alignment-free similarity searches, and in clustering of large and/or divergent sequence sets. Second, a feature space defined by quantitative properties can be used in comparative studies of protein families and organisms. Third, the feature space can be used for evaluating generative models, where large number of sequences generated by the model can be compared to actually observed sequences.http://link.springer.com/article/10.1186/s12859-017-1751-4Protein sequence analysisPython packageQuantitative propertiesQuantitative recurrence analysisn-grams |
| spellingShingle | Bogumił M. Konopka Marta Marciniak Witold Dyrka Quantiprot - a Python package for quantitative analysis of protein sequences BMC Bioinformatics Protein sequence analysis Python package Quantitative properties Quantitative recurrence analysis n-grams |
| title | Quantiprot - a Python package for quantitative analysis of protein sequences |
| title_full | Quantiprot - a Python package for quantitative analysis of protein sequences |
| title_fullStr | Quantiprot - a Python package for quantitative analysis of protein sequences |
| title_full_unstemmed | Quantiprot - a Python package for quantitative analysis of protein sequences |
| title_short | Quantiprot - a Python package for quantitative analysis of protein sequences |
| title_sort | quantiprot a python package for quantitative analysis of protein sequences |
| topic | Protein sequence analysis Python package Quantitative properties Quantitative recurrence analysis n-grams |
| url | http://link.springer.com/article/10.1186/s12859-017-1751-4 |
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