新規登録 | ログイン | FAQ      [?] 
Recent | Recommended | Search | Authors | Tags | Export

Group: SGU-CIPF - with tag structure_prediction [64 articles]

グループ SGU-CIPF のメンバーが最近追加した論文の一覧 with tag structure_prediction
  • Automated de novo prediction of native-like RNA tertiary structures
    PNAS (28 August 2007), 0703836104.
    by Rhiju Das, David Baker
  • Computer modeling 16 S ribosomal RNA
    Journal of Molecular Biology, Vol. 221, No. 3. (5 October 1991), pp. 889-907.
    by John M Hubbard, John E Hearst
  • Prediction of protein three-dimensional structures in insertion and deletion regions: a procedure for searching data bases of representative protein fragments using geometric scoring criteria.
    J Mol Biol, Vol. 253, No. 1. (13 October 1995), pp. 114-131.
  • Facilitating RNA structure prediction with microarrays.
    Biochemistry, Vol. 45, No. 2. (17 January 2006), pp. 581-593.
    by E Kierzek, R Kierzek, DH Turner, IE Catrina
  • Derivation of rules for comparative protein modeling from a database of protein structure alignments.
    Protein Sci, Vol. 3, No. 9. (September 1994), pp. 1582-1596.
    by A Sali, JP Overington
  • Towards genome-scale structure prediction for transmembrane proteins.
    Philos Trans R Soc Lond B Biol Sci, Vol. 361, No. 1467. (29 March 2006), pp. 465-475.
  • Modeling the three-dimensional structure of RNA.
    FASEB J, Vol. 7, No. 1. (January 1993), pp. 97-105.
  • High-resolution protein folding with a transferable potential
    PNAS, Vol. 102, No. 52. (27 December 2005), pp. 18914-18919.
    by Isaac A Hubner, Eric J Deeds, Eugene I Shakhnovich
  • The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling
    Bioinformatics, Vol. 22, No. 2. (15 January 2006), pp. 195-201.
    by Konstantin Arnold, Lorenza Bordoli, Jurgen Kopp, Torsten Schwede
  • Grow to Fit Molecular Dynamics (G2FMD): an ab initio method for protein side-chain assignment and refinement
    Protein Engineering, Design and Selection, Vol. 19, No. 2. (February 2006), pp. 55-65.
    by Wei Zhang, Yong Duan
  • Combining evolutionary and structural information for local protein structure prediction.
    Proteins, Vol. 56, No. 4. (1 September 2004), pp. 782-794.
    by J Pei, NV Grishin
  • Five hierarchical levels of sequence-structure correlation in proteins.
    Appl Bioinformatics, Vol. 3, No. 2-3. (2004), pp. 97-104.
    by C Bystroff, Y Shao, X Yuan
  • Evolutionarily Conserved Pathways of Energetic Connectivity in Protein Families
    Science, Vol. 286, No. 5438. (08 October 1999), pp. 295-299.
    by Steve W Lockless, Rama Ranganathan
  • Evolutionarily conserved networks of residues mediate allosteric communication in proteins.
    Nat Struct Biol, Vol. 10, No. 1. (January 2003), pp. 59-69.
    by GM Süel, SW Lockless, MA Wall, R Ranganathan
  • Local complexity of amino acid interactions in a protein core.
    Proc Natl Acad Sci U S A, Vol. 101, No. 1. (6 January 2004), pp. 111-116.
    by RK Jain, R Ranganathan
  • Natural-like function in artificial WW domains
    Nature, Vol. 437, No. 7058., pp. 579-583.
    by William P Russ, Drew M Lowery, Prashant Mishra, Michael B Yaffe, Rama Ranganathan
  • The SWISS-MODEL Repository: new features and functionalities.
    Nucleic Acids Res, Vol. 34, No. Database issue. (1 January 2006)
    by J Kopp, T Schwede
  • Modeling RNA tertiary structure from patterns of sequence variation.
    Methods Enzymol, Vol. 317 (2000), pp. 491-510.
    by F Michel, M Costa, C Massire, E Westhof
    posted to review rna structure_prediction by marcius to the group SGU-CIPF on 2005-12-22 22:45:59 as ** along with 1 group BioinfoCIPF
  • Practical lessons from protein structure prediction.
    Nucleic Acids Res, Vol. 33, No. 6. (2005), pp. 1874-1891.
  • Protein structure prediction in genomics.
    Brief Bioinform, Vol. 2, No. 2. (May 2001), pp. 111-125.
    by DT Jones
    posted to review structural_genomics structure_prediction by marcius to the group SGU-CIPF on 2005-12-22 06:51:11 as ** along with 1 group BioinfoCIPF
  • Structural genomics analysis of alternative splicing and application to isoform structure modeling.
    Proc Natl Acad Sci U S A (14 December 2005)
    by Peng Wang, Bo Yan, Jun-Tao T Guo, Chindo Hicks, Ying Xu
  • Protein structure prediction: inroads to biology.
    Mol Cell, Vol. 20, No. 6. (22 December 2005), pp. 811-819.
    by D Petrey, B Honig
  • The relation between the divergence of sequence and structure in proteins.
    EMBO J, Vol. 5, No. 4. (April 1986), pp. 823-826.
    by C Chothia, AM Lesk
  • Toward High-Resolution de Novo Structure Prediction for Small Proteins
    Science, Vol. 309, No. 5742. (16 September 2005), pp. 1868-1871.
    by Philip Bradley, Kira M Misura, David Baker
  • Progress in Modeling of Protein Structures and Interactions
    Science, Vol. 310, No. 5748. (28 October 2005), pp. 638-642.
    by Ora Schueler-Furman, Chu Wang, Phil Bradley, Kira Misura, David Baker
  • Structure-derived hydrophobic potential. Hydrophobic potential derived from X-ray structures of globular proteins is able to identify native folds.
    J Mol Biol, Vol. 224, No. 3. (5 April 1992), pp. 725-732.
    by G Casari, MJ Sippl
  • Boltzmann's principle, knowledge-based mean fields and protein folding. An approach to the computational determination of protein structures.
    J Comput Aided Mol Des, Vol. 7, No. 4. (August 1993), pp. 473-501.
    by MJ Sippl
  • Knowledge-based potentials for proteins.
    Curr Opin Struct Biol, Vol. 5, No. 2. (April 1995), pp. 229-235.
    by MJ Sippl
  • Threading thrills and threats.
    Structure, Vol. 4, No. 1. (15 January 1996), pp. 15-19.
    by MJ Sippl, H Flöckner
  • Empirical potentials and functions for protein folding and binding.
    Curr Opin Struct Biol, Vol. 7, No. 2. (April 1997), pp. 222-228.
    by S Vajda, M Sippl, J Novotny
  • Theory and simulation. Old problems, new paradigms.
    Curr Opin Struct Biol, Vol. 7, No. 2. (April 1997), pp. 179-180.
    by J Novotny, M Sippl
  • The role of protein structure in genomics.
    FEBS Lett, Vol. 476, No. 1-2. (30 June 2000), pp. 98-102.
  • Knowledge-based potentials--back to the roots.
    Biochemistry (Mosc), Vol. 63, No. 3. (March 1998), pp. 247-252.
  • Assessment of CASP6 predictions for new and nearly new fold targets.
    Proteins (26 September 2005)
    by James J J Vincent, Chin-Hsien H Tai, B K K Sathyanarayana, Byungkook Lee
  • Generalized protein structure prediction based on combination of fold-recognition with de novo folding and evaluation of models.
    Proteins (26 September 2005)
    by Andrzej Koliński, Janusz M M Bujnicki
  • Protein structure prediction in CASP6 using CHIMERA and FAMS.
    Proteins (26 September 2005)
    by Mayuko Takeda-Shitaka, Genki Terashi, Daisuke Takaya, Kazuhiko Kanou, Mitsuo Iwadate, Hideaki Umeyama
  • Protein structure prediction using a variety of profile libraries and 3D verification.
    Proteins (26 September 2005)
    by Kentaro Tomii, Takatsugu Hirokawa, Chie Motono
  • SAM-T04: what's new in protein-structure prediction for CASP6.
    Proteins (26 September 2005)
    by Kevin Karplus, Sol Katzman, George Shackleford, Martina Koeva, Jenny Draper, Bret Barnes, Marcia Soriano, Richard Hughey
  • Protein loop structure prediction with flexible stem geometries.
    Proteins (12 October 2005)
    by M Mönnigmann, C A A Floudas
  • Assessment of predictions submitted for the CASP6 comparative modelling category.
    Proteins (26 September 2005)
    by Michael Tress, Iakes Ezkurdia, Osvaldo Graña, Gonzalo López, Alfonso Valencia
  • Free modeling with Rosetta in CASP6.
    Proteins (26 September 2005)
    by Philip Bradley, Lars Malmström, Bin Qian, Jack Schonbrun, Dylan Chivian, David E E Kim, Jens Meiler, Kira M S M Misura, David Baker
  • Prediction of novel and analogous folds using fragment assembly and fold recognition.
    Proteins (26 September 2005)
    by D T T Jones, K Bryson, A Coleman, L J J McGuffin, M I I Sadowski, J S S Sodhi, J J J Ward
  • SPARKS 2 and SP(3) servers in CASP 6.
    Proteins (26 September 2005)
    by Hongyi Zhou, Yaoqi Zhou
  • Progress over the first decade of CASP experiments.
    Proteins (26 September 2005)
    by Andriy Kryshtafovych, Ceslovas Venclovas, Krzysztof Fidelis, John Moult
  • Improvement of comparative model accuracy by free-energy optimization along principal components of natural structural variation.
    Proc Natl Acad Sci U S A, Vol. 101, No. 43. (26 October 2004), pp. 15346-15351.
    by B Qian, AR Ortiz, D Baker
  • Have we seen all structures corresponding to short protein fragments in the Protein Data Bank? An update.
    Protein Eng, Vol. 16, No. 6. (June 2003), pp. 407-414.
    by P Du, M Andrec, RM Levy
    posted to protein_fragments structure_prediction by marcius to the group SGU-CIPF on 2005-10-22 03:09:41 as ** along with 1 group BioinfoCIPF
  • Structure prediction of membrane proteins.
    Genomics Proteomics Bioinformatics, Vol. 2, No. 1. (February 2004), pp. 1-5.
    by C Zhou, Y Zheng, Y Zhou
  • State-of-the-art in membrane protein prediction.
    Appl Bioinformatics, Vol. 1, No. 1. (2002), pp. 21-35.
    by CP Chen, B Rost
  • Hamiltonians for protein tertiary structure prediction based on three-dimensional environment principles.
    J Mol Biol, Vol. 233, No. 3. (October 1993), pp. 480-487.
    by T Madej, MC Mossing
  • Computational analysis of alpha-helical membrane protein structure: implications for the prediction of 3D structural models.
    Protein Eng Des Sel, Vol. 17, No. 8. (August 2004), pp. 613-624.
    by TA Eyre, L Partridge, JM Thornton
  • 注: このページを引用する時は次のURLでどうぞ: http://www.citeulike.org/group/1570/tag/structure_prediction

    Result page: 1 2 Next RIS BibTeX RSS
    CiteULike organises scholarly (or academic) papers or literature and provides bibliographic (which means it makes bibliographies) for universities and higher education establishments. It helps undergraduates and postgraduates. People studying for PhDs or in postdoctoral (postdoc) positions. The service is similar in scope to EndNote or RefWorks or any other reference manager like BibTeX, but it is a social bookmarking service for scientists and humanities researchers.