Covariation of mutations: A computational approach for determination of function and structure from sequence

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The authors have developed and enhanced a set of tools for fold recognition with hidden Markov models (HMMs), and used these tools effectively in the CASP2 protein structure prediction contest [KKB+97]. HMMs have limitations, and one limitation is that they do not model the long-range pairwise interactions that define the shape of a protein. As such, the authors are working on modeling pairwise interactions to incorporate them into the HMM-based framework. Classical fold recognition methods are based on the premise of distinct pairwise preferences between two given amino acids. The authors have studied these preferences extensively and found that in ... continued below

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13 p.

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Haussler, D.; Hughey, R.; Karplus, K.; Cline, M.; Grate, L.; Kulp, D. et al. November 1, 1998.

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Description

The authors have developed and enhanced a set of tools for fold recognition with hidden Markov models (HMMs), and used these tools effectively in the CASP2 protein structure prediction contest [KKB+97]. HMMs have limitations, and one limitation is that they do not model the long-range pairwise interactions that define the shape of a protein. As such, the authors are working on modeling pairwise interactions to incorporate them into the HMM-based framework. Classical fold recognition methods are based on the premise of distinct pairwise preferences between two given amino acids. The authors have studied these preferences extensively and found that in the general case, this information is limited. Yet by modeling pairwise interactions in context of phylogenetic relationships and by modeling one specific type of contact, the contact between interacting beta strand residues, they have recovered significant information for prediction and analysis of protein structure.

Physical Description

13 p.

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OSTI as DE99000809

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  • Other Information: PBD: [1998]

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  • Other: DE99000809
  • Report No.: LA-UR--98-2180
  • Grant Number: W-7405-ENG-36
  • DOI: 10.2172/674904 | External Link
  • Office of Scientific & Technical Information Report Number: 674904
  • Archival Resource Key: ark:/67531/metadc704400

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Creation Date

  • November 1, 1998

Added to The UNT Digital Library

  • Sept. 12, 2015, 6:31 a.m.

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  • May 5, 2016, 6:24 p.m.

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Haussler, D.; Hughey, R.; Karplus, K.; Cline, M.; Grate, L.; Kulp, D. et al. Covariation of mutations: A computational approach for determination of function and structure from sequence, report, November 1, 1998; New Mexico. (digital.library.unt.edu/ark:/67531/metadc704400/: accessed July 21, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.