background: boophilus tick is responsible for the transmission of some pathogens (types of germs) and the reduction of fertility in cattles. tropomyosin protein plays an important role in regulating actin function, immune and allergic reactions and vaccine production. objectives: accurate identification of antigenic determinants (epitopes) is difficult, time consuming and not economic, thus we ...

JPred4 (http://www.compbio.dundee.ac.uk/jpred4) is the latest version of the popular JPred protein secondary structure prediction server which provides predictions by the JNet algorithm, one of the most accurate methods for secondary structure prediction. In addition to protein secondary structure, JPred also makes predictions of solvent accessibility and coiled-coil regions. The JPred service ...

During molecular recognition of proteins in biological systems, helices, reverse turns, and beta-sheets are dominant motifs. Often there are therapeutic reasons for blocking such recognition sites, and significant progress has been made by medicinal chemists in the design and synthesis of semirigid molecular scaffolds on which to display amino acid side chains. The basic premise is that preorga...

Accurately aligning distant protein sequences is notoriously difficult. Since the amino acid sequence alone often does not provide enough information to obtain accurate alignments under the standard alignment scoring functions, a recent approach to improving alignment accuracy is to use additional information such as secondary structure. We make several advances in alignment of protein sequence...

The combination of classifiers has been proposed as a method to improve the accuracy achieved by a single classifier. In this study, the performances of optimistic and pessimistic ordered weighted averaging operators for protein secondary structure classifiers fusion have been investigated. Each secondary structure classifier outputs a unique structure for each input residue. We used confusion ...

In this paper we study the performance of probabilistic networks in the context of protein sequence analysis in molecular biology. Speci cally, we report the results of our initial experiments applying this framework to the problem of protein secondary structure prediction. One of the main advantages of the probabilistic approach we describe here is our ability to perform detailed experiments w...

In this paper we study the performance of probabilistic networks in the context of protein sequence analysis in molecular biology. Specifically, we report the results of our initial experiments applying this framework to the problem of protein secondary structure prediction. One of the main advantages of the probabilistic approach we describe here is our ability to perform detailed experiments ...

For certain categories of sequences, information from both the past and the future can be used for analysis and predictions at time t. This is the case for biological sequences where the nature and function of a region in a sequence may strongly depend on events located both upstream and downstream. We develop a new family of adaptive graphical model architectures for learning non-causal sequen...

Proteins are linear chain biomolecules composed of 20 different amino acids which form secondary structures such as helixes and loops [8]. Here, we use deep recurrent memory networks and deep convectional networks for predicting secondary structure annotations on sequences from the Uniprot database. We compare different network architectures and memory models, and discuss possible improvements....

A physical theory of protein secondary structure is proposed and tested by performing exceedingly simple Monte Carlo simulations. In essence, secondary structure propensities are predominantly a consequence of two competing local effects, one favoring hydrogen bond formation in helices and turns, the other opposing the attendant reduction in sidechain conformational entropy on helix and turn fo...