منابع مشابه
Automatic Discovery of Protein Motifs
We have developed a novel representation of protein motifs that permits the rapid discovery of structural features in sets of protein sequences with a common structure or function. Many popular methods for representing protein motifs (consensus sequences, weight matrices, profiles, etc.) emphasize conservation of amino acids at specific sites in the sequence. Our method looks for correlations b...
متن کاملKnowledge Discovery of Multilevel Protein Motifs
A new category of protein motif is introduced. This type of motif captures, in addition to global structure, the nested structure of its component parts. A dataset of four proteins is represented using this scheme. A structured machine discovery procedure is used to discover recurrent amino acid motifs and this knowledge is utilized for the expression of subsequent protein motif discoveries. Ex...
متن کاملRepresentation for Discovery of Protein Motifs
There are several dimensions and levels of complexity in which information on protein motifs may be available. For example, one-dimensional sequence motifs may be associated with secondary structure identifiers. Alternatively, three-dimensional information on polypeptide segments may be used to induce prototypical three-dimensional structure templates. This paper surveys various representations...
متن کاملAutomatic Discovery of Protein Motifs Using Genetic Programming
Automated methods of machine learning may prove to be useful in discovering biologically meaningful information hidden in the rapidly growing databases of DNA sequences and protein sequences. Genetic programming is an extension of the genetic algorithm in which a population of computer programs is bred, over a series of generations, in order to solve a problem. Genetic programming is capable of...
متن کاملAutomated discovery of 3D motifs for protein function annotation
MOTIVATION Function inference from structure is facilitated by the use of patterns of residues (3D motifs), normally identified by expert knowledge, that correlate with function. As an alternative to often limited expert knowledge, we use machine-learning techniques to identify patterns of 3-10 residues that maximize function prediction. This approach allows us to test the assumption that resid...
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ژورنال
عنوان ژورنال: Machine Learning
سال: 1995
ISSN: 0885-6125,1573-0565
DOI: 10.1007/bf00993382