References of "Rost, B"
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See detailPaving the future: finding suitable ISMB venues
Rost, B.; Gaasterland, T.; Lengauer, T. et al

in Bioinformatics (2012), 28(19), 2556-9

ISCB, the International Society for Computational Biology, organizes the largest event in the field of computational biology and bioinformatics, namely the annual ISMB, the international conference on ... [more ▼]

ISCB, the International Society for Computational Biology, organizes the largest event in the field of computational biology and bioinformatics, namely the annual ISMB, the international conference on Intelligent Systems for Molecular Biology. This year at ISMB 2012 in Long Beach, ISCB celebrated the 20th anniversary of its flagship meeting. ISCB is a young, lean and efficient society that aspires to make a significant impact with only limited resources. Many constraints make the choice of venues for ISMB a tough challenge. Here, we describe those challenges and invite the contribution of ideas for solutions. [less ▲]

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See detailBeyond annotation transfer by homology: novel protein-function prediction methods to assist drug discovery
Ofran, Y.; Punta, M.; Schneider, Reinhard UL et al

in Drug Discovery Today (2005), 10(21), 1475-1482

Every entirely sequenced genome reveals 100s to 1000s of protein sequences for which the only annotation available is 'hypothetical protein'. Thus, in the human genome and in the genomes of pathogenic ... [more ▼]

Every entirely sequenced genome reveals 100s to 1000s of protein sequences for which the only annotation available is 'hypothetical protein'. Thus, in the human genome and in the genomes of pathogenic agents there could be 1000s of potential, unexplored drug targets. Computational prediction of protein function can play a role in studying these targets. We shall review the challenges, research approaches and recently developed tools in the field of computational function-prediction and we will discuss the ways these issues can change the process of drug discovery. [less ▲]

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See detailPedestrian guide to analyzing sequence databases
Rost, B.; Schneider, Reinhard UL; Sander, C.

in WWW-publication (1997)

Over the past few years our means of communication have changed rapidly due to the growth of the World Wide Web (WWW). The Web enables molecular biologists to immediately access databases, scan literature ... [more ▼]

Over the past few years our means of communication have changed rapidly due to the growth of the World Wide Web (WWW). The Web enables molecular biologists to immediately access databases, scan literature, find information about related research and researchers, and to trace cell cultures. Wet-lab biologists can uncover information about the protein of interest without having to become experts in sequence analysis. Here, we present a variety of tools; provide an overview of the state-of-the art in sequence analysis; and described some of the principles of the methods. [less ▲]

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See detailProtein fold recognition by prediction-based threading
Rost, B.; Schneider, Reinhard UL; Sander, C.

in Journal of Molecular Biology (1997), 270(3), 471-480

In fold recognition by threading one takes the amino acid sequence of a protein and evaluates how well it fits into one of the known three-dimensional (3D) protein structures. The quality of sequence ... [more ▼]

In fold recognition by threading one takes the amino acid sequence of a protein and evaluates how well it fits into one of the known three-dimensional (3D) protein structures. The quality of sequence-structure fit is typically evaluated using inter-residue potentials of mean force or other statistical parameters. Here, we present an alternative approach to evaluating sequence-structure fitness. Starting from the amino acid sequence we first predict secondary structure and solvent accessibility for each residue. We then thread the resulting one-dimensional (1D) profile of predicted structure assignments into each of the known 3D structures. The optimal threading for each sequence-structure pair is obtained using dynamic programming. The overall best sequence-structure pair constitutes the predicted 3D structure for the input sequence. The method is fine-tuned by adding information from direct sequence-sequence comparison and applying a series of empirical filters. Although the method relies on reduction of 3D information into 1D structure profiles, its accuracy is, surprisingly, not clearly inferior to methods based on evaluation of residue interactions in 3D. We therefore hypothesise that existing 1D-3D threading methods essentially do not capture more than the fitness of an amino acid sequence for a particular 1D succession of secondary structure segments and residue solvent accessibility. The prediction-based threading method on average finds any structurally homologous region at first rank in 29% of the cases (including sequence information). For the 22% first hits detected at highest scores, the expected accuracy rose to 75%. However, the task of detecting entire folds rather than homologous fragments was managed much better; 45 to 75% of the first hits correctly recognised the fold. [less ▲]

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See detailPHD - AN AUTOMATIC MAIL SERVER FOR PROTEIN SECONDARY STRUCTURE PREDICTION
ROST, B.; SANDER, C.; Schneider, Reinhard UL

in Computer Applications in the Biosciences [=CABIOS] (1994), 10(1), 53-60

By the middle of 1993, > 30000 protein sequences had been listed. For 1000 of these, the three-dimensional (tertiary) structure has been experimentally solved. Another 7000 can be modelled by homology ... [more ▼]

By the middle of 1993, > 30000 protein sequences had been listed. For 1000 of these, the three-dimensional (tertiary) structure has been experimentally solved. Another 7000 can be modelled by homology. For the remaining 21000 sequences, secondary structure prediction provides a rough estimate of structural features. Predictions in three states range between 35% (random) and 88% (homology modelling) overall accuracy. Using information about evolutionary conservation as contained in multiple sequence alignments, the secondary structure of 4700 protein sequences was predicted by the automatic e-mail sewer PHD, For proteins with at least one known homologue, the method has an expected overall three-state accuracy of 71.4% for proteins with at least one known homologue (evaluated on 126 unique protein chains). [less ▲]

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See detailREDEFINING THE GOALS OF PROTEIN SECONDARY STRUCTURE PREDICTION
ROST, B.; SANDER, C.; Schneider, Reinhard UL

in Journal of Molecular Biology (1994), 235(1), 13-26

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See detailEvolution and Neural Networks – Protein Secondary Structure Prediction Above 71% Accuracy
Rost, B.; Sander, C.; Schneider, Reinhard UL

in Proceedings of the 27th Hawaii International Conference on System Sciences, Vol. V, Biotechnology Computing (1994)

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See detailPROGRESS IN PROTEIN-STRUCTURE PREDICTION
ROST, B.; Schneider, Reinhard UL; SANDER, C.

in Trends in Biochemical Sciences - Regular Edition (1993), 18(4), 120-123

Prediction of protein secondary structure is an old problem and progress has been slow. Recently, spectacular success has been claimed in the blind prediction of the catalytic subunit of the cAMP ... [more ▼]

Prediction of protein secondary structure is an old problem and progress has been slow. Recently, spectacular success has been claimed in the blind prediction of the catalytic subunit of the cAMP-dependent protein kinase. When predictions in this and other test cases are assessed critically, some claims of prediction success turn out to be exaggerated, but a kernel of real progress remains: protein structure prediction can be improved substantially when a family of related sequences is available. Enough so that molecular biologists equipped with a new amino acid sequence and a multiple sequence alignment in hand may be tempted to test the new prediction methods. [less ▲]

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