The MULTICOM toolbox for protein structure prediction
Background As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or < 0.07%) have solved tertiary structures determined by...
Ausführliche Beschreibung
Autor*in: |
Cheng, Jianlin [verfasserIn] |
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E-Artikel |
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Englisch |
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2012 |
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Anmerkung: |
© Cheng et al.; licensee BioMed Central Ltd. 2012 |
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Übergeordnetes Werk: |
Enthalten in: BMC bioinformatics - London : BioMed Central, 2000, 13(2012), 1 vom: 30. Apr. |
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Übergeordnetes Werk: |
volume:13 ; year:2012 ; number:1 ; day:30 ; month:04 |
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DOI / URN: |
10.1186/1471-2105-13-65 |
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Katalog-ID: |
SPR026876272 |
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520 | |a Background As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or < 0.07%) have solved tertiary structures determined by experimental techniques. The gap between protein sequence and structure continues to enlarge rapidly as the throughput of genome sequencing techniques is much higher than that of protein structure determination techniques. Computational software tools for predicting protein structure and structural features from protein sequences are crucial to make use of this vast repository of protein resources. Results To meet the need, we have developed a comprehensive MULTICOM toolbox consisting of a set of protein structure and structural feature prediction tools. These tools include secondary structure prediction, solvent accessibility prediction, disorder region prediction, domain boundary prediction, contact map prediction, disulfide bond prediction, beta-sheet topology prediction, fold recognition, multiple template combination and alignment, template-based tertiary structure modeling, protein model quality assessment, and mutation stability prediction. Conclusions These tools have been rigorously tested by many users in the last several years and/or during the last three rounds of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7-9) from 2006 to 2010, achieving state-of-the-art or near performance. In order to facilitate bioinformatics research and technological development in the field, we have made the MULTICOM toolbox freely available as web services and/or software packages for academic use and scientific research. It is available at http://sysbio.rnet.missouri.edu/multicom_toolbox/. | ||
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650 | 4 | |a Secondary structure |7 (dpeaa)DE-He213 | |
650 | 4 | |a Solvent accessibility |7 (dpeaa)DE-He213 | |
650 | 4 | |a Domain |7 (dpeaa)DE-He213 | |
650 | 4 | |a Contact map |7 (dpeaa)DE-He213 | |
650 | 4 | |a Tertiary structure |7 (dpeaa)DE-He213 | |
650 | 4 | |a Protein model quality assessment |7 (dpeaa)DE-He213 | |
650 | 4 | |a Fold recognition |7 (dpeaa)DE-He213 | |
650 | 4 | |a Protein disorder |7 (dpeaa)DE-He213 | |
700 | 1 | |a Li, Jilong |4 aut | |
700 | 1 | |a Wang, Zheng |4 aut | |
700 | 1 | |a Eickholt, Jesse |4 aut | |
700 | 1 | |a Deng, Xin |4 aut | |
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10.1186/1471-2105-13-65 doi (DE-627)SPR026876272 (SPR)1471-2105-13-65-e DE-627 ger DE-627 rakwb eng Cheng, Jianlin verfasserin aut The MULTICOM toolbox for protein structure prediction 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Cheng et al.; licensee BioMed Central Ltd. 2012 Background As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or < 0.07%) have solved tertiary structures determined by experimental techniques. The gap between protein sequence and structure continues to enlarge rapidly as the throughput of genome sequencing techniques is much higher than that of protein structure determination techniques. Computational software tools for predicting protein structure and structural features from protein sequences are crucial to make use of this vast repository of protein resources. Results To meet the need, we have developed a comprehensive MULTICOM toolbox consisting of a set of protein structure and structural feature prediction tools. These tools include secondary structure prediction, solvent accessibility prediction, disorder region prediction, domain boundary prediction, contact map prediction, disulfide bond prediction, beta-sheet topology prediction, fold recognition, multiple template combination and alignment, template-based tertiary structure modeling, protein model quality assessment, and mutation stability prediction. Conclusions These tools have been rigorously tested by many users in the last several years and/or during the last three rounds of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7-9) from 2006 to 2010, achieving state-of-the-art or near performance. In order to facilitate bioinformatics research and technological development in the field, we have made the MULTICOM toolbox freely available as web services and/or software packages for academic use and scientific research. It is available at http://sysbio.rnet.missouri.edu/multicom_toolbox/. Protein structure prediction (dpeaa)DE-He213 Bioinformatics tool (dpeaa)DE-He213 Secondary structure (dpeaa)DE-He213 Solvent accessibility (dpeaa)DE-He213 Domain (dpeaa)DE-He213 Contact map (dpeaa)DE-He213 Tertiary structure (dpeaa)DE-He213 Protein model quality assessment (dpeaa)DE-He213 Fold recognition (dpeaa)DE-He213 Protein disorder (dpeaa)DE-He213 Li, Jilong aut Wang, Zheng aut Eickholt, Jesse aut Deng, Xin aut Enthalten in BMC bioinformatics London : BioMed Central, 2000 13(2012), 1 vom: 30. Apr. (DE-627)326644814 (DE-600)2041484-5 1471-2105 nnns volume:13 year:2012 number:1 day:30 month:04 https://dx.doi.org/10.1186/1471-2105-13-65 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2012 1 30 04 |
spelling |
10.1186/1471-2105-13-65 doi (DE-627)SPR026876272 (SPR)1471-2105-13-65-e DE-627 ger DE-627 rakwb eng Cheng, Jianlin verfasserin aut The MULTICOM toolbox for protein structure prediction 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Cheng et al.; licensee BioMed Central Ltd. 2012 Background As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or < 0.07%) have solved tertiary structures determined by experimental techniques. The gap between protein sequence and structure continues to enlarge rapidly as the throughput of genome sequencing techniques is much higher than that of protein structure determination techniques. Computational software tools for predicting protein structure and structural features from protein sequences are crucial to make use of this vast repository of protein resources. Results To meet the need, we have developed a comprehensive MULTICOM toolbox consisting of a set of protein structure and structural feature prediction tools. These tools include secondary structure prediction, solvent accessibility prediction, disorder region prediction, domain boundary prediction, contact map prediction, disulfide bond prediction, beta-sheet topology prediction, fold recognition, multiple template combination and alignment, template-based tertiary structure modeling, protein model quality assessment, and mutation stability prediction. Conclusions These tools have been rigorously tested by many users in the last several years and/or during the last three rounds of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7-9) from 2006 to 2010, achieving state-of-the-art or near performance. In order to facilitate bioinformatics research and technological development in the field, we have made the MULTICOM toolbox freely available as web services and/or software packages for academic use and scientific research. It is available at http://sysbio.rnet.missouri.edu/multicom_toolbox/. Protein structure prediction (dpeaa)DE-He213 Bioinformatics tool (dpeaa)DE-He213 Secondary structure (dpeaa)DE-He213 Solvent accessibility (dpeaa)DE-He213 Domain (dpeaa)DE-He213 Contact map (dpeaa)DE-He213 Tertiary structure (dpeaa)DE-He213 Protein model quality assessment (dpeaa)DE-He213 Fold recognition (dpeaa)DE-He213 Protein disorder (dpeaa)DE-He213 Li, Jilong aut Wang, Zheng aut Eickholt, Jesse aut Deng, Xin aut Enthalten in BMC bioinformatics London : BioMed Central, 2000 13(2012), 1 vom: 30. Apr. (DE-627)326644814 (DE-600)2041484-5 1471-2105 nnns volume:13 year:2012 number:1 day:30 month:04 https://dx.doi.org/10.1186/1471-2105-13-65 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2012 1 30 04 |
allfields_unstemmed |
10.1186/1471-2105-13-65 doi (DE-627)SPR026876272 (SPR)1471-2105-13-65-e DE-627 ger DE-627 rakwb eng Cheng, Jianlin verfasserin aut The MULTICOM toolbox for protein structure prediction 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Cheng et al.; licensee BioMed Central Ltd. 2012 Background As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or < 0.07%) have solved tertiary structures determined by experimental techniques. The gap between protein sequence and structure continues to enlarge rapidly as the throughput of genome sequencing techniques is much higher than that of protein structure determination techniques. Computational software tools for predicting protein structure and structural features from protein sequences are crucial to make use of this vast repository of protein resources. Results To meet the need, we have developed a comprehensive MULTICOM toolbox consisting of a set of protein structure and structural feature prediction tools. These tools include secondary structure prediction, solvent accessibility prediction, disorder region prediction, domain boundary prediction, contact map prediction, disulfide bond prediction, beta-sheet topology prediction, fold recognition, multiple template combination and alignment, template-based tertiary structure modeling, protein model quality assessment, and mutation stability prediction. Conclusions These tools have been rigorously tested by many users in the last several years and/or during the last three rounds of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7-9) from 2006 to 2010, achieving state-of-the-art or near performance. In order to facilitate bioinformatics research and technological development in the field, we have made the MULTICOM toolbox freely available as web services and/or software packages for academic use and scientific research. It is available at http://sysbio.rnet.missouri.edu/multicom_toolbox/. Protein structure prediction (dpeaa)DE-He213 Bioinformatics tool (dpeaa)DE-He213 Secondary structure (dpeaa)DE-He213 Solvent accessibility (dpeaa)DE-He213 Domain (dpeaa)DE-He213 Contact map (dpeaa)DE-He213 Tertiary structure (dpeaa)DE-He213 Protein model quality assessment (dpeaa)DE-He213 Fold recognition (dpeaa)DE-He213 Protein disorder (dpeaa)DE-He213 Li, Jilong aut Wang, Zheng aut Eickholt, Jesse aut Deng, Xin aut Enthalten in BMC bioinformatics London : BioMed Central, 2000 13(2012), 1 vom: 30. Apr. (DE-627)326644814 (DE-600)2041484-5 1471-2105 nnns volume:13 year:2012 number:1 day:30 month:04 https://dx.doi.org/10.1186/1471-2105-13-65 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2012 1 30 04 |
allfieldsGer |
10.1186/1471-2105-13-65 doi (DE-627)SPR026876272 (SPR)1471-2105-13-65-e DE-627 ger DE-627 rakwb eng Cheng, Jianlin verfasserin aut The MULTICOM toolbox for protein structure prediction 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Cheng et al.; licensee BioMed Central Ltd. 2012 Background As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or < 0.07%) have solved tertiary structures determined by experimental techniques. The gap between protein sequence and structure continues to enlarge rapidly as the throughput of genome sequencing techniques is much higher than that of protein structure determination techniques. Computational software tools for predicting protein structure and structural features from protein sequences are crucial to make use of this vast repository of protein resources. Results To meet the need, we have developed a comprehensive MULTICOM toolbox consisting of a set of protein structure and structural feature prediction tools. These tools include secondary structure prediction, solvent accessibility prediction, disorder region prediction, domain boundary prediction, contact map prediction, disulfide bond prediction, beta-sheet topology prediction, fold recognition, multiple template combination and alignment, template-based tertiary structure modeling, protein model quality assessment, and mutation stability prediction. Conclusions These tools have been rigorously tested by many users in the last several years and/or during the last three rounds of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7-9) from 2006 to 2010, achieving state-of-the-art or near performance. In order to facilitate bioinformatics research and technological development in the field, we have made the MULTICOM toolbox freely available as web services and/or software packages for academic use and scientific research. It is available at http://sysbio.rnet.missouri.edu/multicom_toolbox/. Protein structure prediction (dpeaa)DE-He213 Bioinformatics tool (dpeaa)DE-He213 Secondary structure (dpeaa)DE-He213 Solvent accessibility (dpeaa)DE-He213 Domain (dpeaa)DE-He213 Contact map (dpeaa)DE-He213 Tertiary structure (dpeaa)DE-He213 Protein model quality assessment (dpeaa)DE-He213 Fold recognition (dpeaa)DE-He213 Protein disorder (dpeaa)DE-He213 Li, Jilong aut Wang, Zheng aut Eickholt, Jesse aut Deng, Xin aut Enthalten in BMC bioinformatics London : BioMed Central, 2000 13(2012), 1 vom: 30. Apr. (DE-627)326644814 (DE-600)2041484-5 1471-2105 nnns volume:13 year:2012 number:1 day:30 month:04 https://dx.doi.org/10.1186/1471-2105-13-65 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2012 1 30 04 |
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10.1186/1471-2105-13-65 doi (DE-627)SPR026876272 (SPR)1471-2105-13-65-e DE-627 ger DE-627 rakwb eng Cheng, Jianlin verfasserin aut The MULTICOM toolbox for protein structure prediction 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Cheng et al.; licensee BioMed Central Ltd. 2012 Background As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or < 0.07%) have solved tertiary structures determined by experimental techniques. The gap between protein sequence and structure continues to enlarge rapidly as the throughput of genome sequencing techniques is much higher than that of protein structure determination techniques. Computational software tools for predicting protein structure and structural features from protein sequences are crucial to make use of this vast repository of protein resources. Results To meet the need, we have developed a comprehensive MULTICOM toolbox consisting of a set of protein structure and structural feature prediction tools. These tools include secondary structure prediction, solvent accessibility prediction, disorder region prediction, domain boundary prediction, contact map prediction, disulfide bond prediction, beta-sheet topology prediction, fold recognition, multiple template combination and alignment, template-based tertiary structure modeling, protein model quality assessment, and mutation stability prediction. Conclusions These tools have been rigorously tested by many users in the last several years and/or during the last three rounds of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7-9) from 2006 to 2010, achieving state-of-the-art or near performance. In order to facilitate bioinformatics research and technological development in the field, we have made the MULTICOM toolbox freely available as web services and/or software packages for academic use and scientific research. It is available at http://sysbio.rnet.missouri.edu/multicom_toolbox/. Protein structure prediction (dpeaa)DE-He213 Bioinformatics tool (dpeaa)DE-He213 Secondary structure (dpeaa)DE-He213 Solvent accessibility (dpeaa)DE-He213 Domain (dpeaa)DE-He213 Contact map (dpeaa)DE-He213 Tertiary structure (dpeaa)DE-He213 Protein model quality assessment (dpeaa)DE-He213 Fold recognition (dpeaa)DE-He213 Protein disorder (dpeaa)DE-He213 Li, Jilong aut Wang, Zheng aut Eickholt, Jesse aut Deng, Xin aut Enthalten in BMC bioinformatics London : BioMed Central, 2000 13(2012), 1 vom: 30. Apr. (DE-627)326644814 (DE-600)2041484-5 1471-2105 nnns volume:13 year:2012 number:1 day:30 month:04 https://dx.doi.org/10.1186/1471-2105-13-65 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2012 1 30 04 |
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Cheng, Jianlin misc Protein structure prediction misc Bioinformatics tool misc Secondary structure misc Solvent accessibility misc Domain misc Contact map misc Tertiary structure misc Protein model quality assessment misc Fold recognition misc Protein disorder The MULTICOM toolbox for protein structure prediction |
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1471-2105 |
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The MULTICOM toolbox for protein structure prediction Protein structure prediction (dpeaa)DE-He213 Bioinformatics tool (dpeaa)DE-He213 Secondary structure (dpeaa)DE-He213 Solvent accessibility (dpeaa)DE-He213 Domain (dpeaa)DE-He213 Contact map (dpeaa)DE-He213 Tertiary structure (dpeaa)DE-He213 Protein model quality assessment (dpeaa)DE-He213 Fold recognition (dpeaa)DE-He213 Protein disorder (dpeaa)DE-He213 |
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misc Protein structure prediction misc Bioinformatics tool misc Secondary structure misc Solvent accessibility misc Domain misc Contact map misc Tertiary structure misc Protein model quality assessment misc Fold recognition misc Protein disorder |
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misc Protein structure prediction misc Bioinformatics tool misc Secondary structure misc Solvent accessibility misc Domain misc Contact map misc Tertiary structure misc Protein model quality assessment misc Fold recognition misc Protein disorder |
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misc Protein structure prediction misc Bioinformatics tool misc Secondary structure misc Solvent accessibility misc Domain misc Contact map misc Tertiary structure misc Protein model quality assessment misc Fold recognition misc Protein disorder |
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The MULTICOM toolbox for protein structure prediction |
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The MULTICOM toolbox for protein structure prediction |
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Cheng, Jianlin Li, Jilong Wang, Zheng Eickholt, Jesse Deng, Xin |
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multicom toolbox for protein structure prediction |
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The MULTICOM toolbox for protein structure prediction |
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Background As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or < 0.07%) have solved tertiary structures determined by experimental techniques. The gap between protein sequence and structure continues to enlarge rapidly as the throughput of genome sequencing techniques is much higher than that of protein structure determination techniques. Computational software tools for predicting protein structure and structural features from protein sequences are crucial to make use of this vast repository of protein resources. Results To meet the need, we have developed a comprehensive MULTICOM toolbox consisting of a set of protein structure and structural feature prediction tools. These tools include secondary structure prediction, solvent accessibility prediction, disorder region prediction, domain boundary prediction, contact map prediction, disulfide bond prediction, beta-sheet topology prediction, fold recognition, multiple template combination and alignment, template-based tertiary structure modeling, protein model quality assessment, and mutation stability prediction. Conclusions These tools have been rigorously tested by many users in the last several years and/or during the last three rounds of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7-9) from 2006 to 2010, achieving state-of-the-art or near performance. In order to facilitate bioinformatics research and technological development in the field, we have made the MULTICOM toolbox freely available as web services and/or software packages for academic use and scientific research. It is available at http://sysbio.rnet.missouri.edu/multicom_toolbox/. © Cheng et al.; licensee BioMed Central Ltd. 2012 |
abstractGer |
Background As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or < 0.07%) have solved tertiary structures determined by experimental techniques. The gap between protein sequence and structure continues to enlarge rapidly as the throughput of genome sequencing techniques is much higher than that of protein structure determination techniques. Computational software tools for predicting protein structure and structural features from protein sequences are crucial to make use of this vast repository of protein resources. Results To meet the need, we have developed a comprehensive MULTICOM toolbox consisting of a set of protein structure and structural feature prediction tools. These tools include secondary structure prediction, solvent accessibility prediction, disorder region prediction, domain boundary prediction, contact map prediction, disulfide bond prediction, beta-sheet topology prediction, fold recognition, multiple template combination and alignment, template-based tertiary structure modeling, protein model quality assessment, and mutation stability prediction. Conclusions These tools have been rigorously tested by many users in the last several years and/or during the last three rounds of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7-9) from 2006 to 2010, achieving state-of-the-art or near performance. In order to facilitate bioinformatics research and technological development in the field, we have made the MULTICOM toolbox freely available as web services and/or software packages for academic use and scientific research. It is available at http://sysbio.rnet.missouri.edu/multicom_toolbox/. © Cheng et al.; licensee BioMed Central Ltd. 2012 |
abstract_unstemmed |
Background As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or < 0.07%) have solved tertiary structures determined by experimental techniques. The gap between protein sequence and structure continues to enlarge rapidly as the throughput of genome sequencing techniques is much higher than that of protein structure determination techniques. Computational software tools for predicting protein structure and structural features from protein sequences are crucial to make use of this vast repository of protein resources. Results To meet the need, we have developed a comprehensive MULTICOM toolbox consisting of a set of protein structure and structural feature prediction tools. These tools include secondary structure prediction, solvent accessibility prediction, disorder region prediction, domain boundary prediction, contact map prediction, disulfide bond prediction, beta-sheet topology prediction, fold recognition, multiple template combination and alignment, template-based tertiary structure modeling, protein model quality assessment, and mutation stability prediction. Conclusions These tools have been rigorously tested by many users in the last several years and/or during the last three rounds of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7-9) from 2006 to 2010, achieving state-of-the-art or near performance. In order to facilitate bioinformatics research and technological development in the field, we have made the MULTICOM toolbox freely available as web services and/or software packages for academic use and scientific research. It is available at http://sysbio.rnet.missouri.edu/multicom_toolbox/. © Cheng et al.; licensee BioMed Central Ltd. 2012 |
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