hoDCA: higher order direct-coupling analysis
Abstract Background Direct-coupling analysis (DCA) is a method for protein contact prediction from sequence information alone. Its underlying principle is parameter estimation for a Hamiltonian interaction function stemming from a maximum entropy model with one- and two-point interactions. Vastly gr...
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| Format: | Article |
| Language: | English |
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BMC
2018-12-01
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| Series: | BMC Bioinformatics |
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| Online Access: | http://link.springer.com/article/10.1186/s12859-018-2583-6 |
| _version_ | 1818156079617409024 |
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| author | Michael Schmidt Kay Hamacher |
| author_facet | Michael Schmidt Kay Hamacher |
| author_sort | Michael Schmidt |
| collection | DOAJ |
| description | Abstract Background Direct-coupling analysis (DCA) is a method for protein contact prediction from sequence information alone. Its underlying principle is parameter estimation for a Hamiltonian interaction function stemming from a maximum entropy model with one- and two-point interactions. Vastly growing sequence databases enable the construction of large multiple sequence alignments (MSA). Thus, enough data exists to include higher order terms, such as three-body correlations. Results We present an implementation of hoDCA, which is an extension of DCA by including three-body interactions into the inverse Ising problem posed by parameter estimation. In a previous study, these three-body-interactions improved contact prediction accuracy for the PSICOV benchmark dataset. Our implementation can be executed in parallel, which results in fast runtimes and makes it suitable for large-scale application. Conclusion Our hoDCA software allows improved contact prediction using the Julia language, leveraging power of multi-core machines in an automated fashion. |
| first_indexed | 2024-12-11T14:52:36Z |
| format | Article |
| id | doaj.art-5492bfff8ad6499d9e13123b7e90d6ac |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-11T14:52:36Z |
| publishDate | 2018-12-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-5492bfff8ad6499d9e13123b7e90d6ac2022-12-22T01:01:24ZengBMCBMC Bioinformatics1471-21052018-12-011911510.1186/s12859-018-2583-6hoDCA: higher order direct-coupling analysisMichael Schmidt0Kay Hamacher1Department of Physics, TU DarmstadtDepartment of Physics, TU DarmstadtAbstract Background Direct-coupling analysis (DCA) is a method for protein contact prediction from sequence information alone. Its underlying principle is parameter estimation for a Hamiltonian interaction function stemming from a maximum entropy model with one- and two-point interactions. Vastly growing sequence databases enable the construction of large multiple sequence alignments (MSA). Thus, enough data exists to include higher order terms, such as three-body correlations. Results We present an implementation of hoDCA, which is an extension of DCA by including three-body interactions into the inverse Ising problem posed by parameter estimation. In a previous study, these three-body-interactions improved contact prediction accuracy for the PSICOV benchmark dataset. Our implementation can be executed in parallel, which results in fast runtimes and makes it suitable for large-scale application. Conclusion Our hoDCA software allows improved contact prediction using the Julia language, leveraging power of multi-core machines in an automated fashion.http://link.springer.com/article/10.1186/s12859-018-2583-6Contact predictionProteinsDCA |
| spellingShingle | Michael Schmidt Kay Hamacher hoDCA: higher order direct-coupling analysis BMC Bioinformatics Contact prediction Proteins DCA |
| title | hoDCA: higher order direct-coupling analysis |
| title_full | hoDCA: higher order direct-coupling analysis |
| title_fullStr | hoDCA: higher order direct-coupling analysis |
| title_full_unstemmed | hoDCA: higher order direct-coupling analysis |
| title_short | hoDCA: higher order direct-coupling analysis |
| title_sort | hodca higher order direct coupling analysis |
| topic | Contact prediction Proteins DCA |
| url | http://link.springer.com/article/10.1186/s12859-018-2583-6 |
| work_keys_str_mv | AT michaelschmidt hodcahigherorderdirectcouplinganalysis AT kayhamacher hodcahigherorderdirectcouplinganalysis |