Current Bioinformatics - Volume 9, Issue 3, 2014

Sequence comparison in the form of alignment plays a crucial role in the area of bioinformatics. However, alignment is commonly restricted by the number of aligned sequences. To address this problem, we presented a 2D pattern matching algorithm for comparing protein sequences. The new algorithm which is an alignment-free comparison is capable of allowing fast comparison even among a large number of protein sequenc Read More

Whole genome sequences are generally accepted as excellent tools for studying evolutionary relationships. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignments could not be directly applied to the whole-genome comparison and phylogenomic studies. There has been a growing interest in alignment-free methods for phylogenetic analysis using co Read More

Using CGR-walk model, this paper studies influenza virus HA/NA protein sequences from 1914 to 2012, and figures out multiple early warning signal values of influenza pandemic outbreak. The variances and lag 2 autocorrelation coefficients of protein sequences obtained according to the detailed HP model of the epidemic outbreak years and the last two years are significantly higher than those of the last adjacent years, w Read More

The generation of a correlation matrix for set of genomic sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. Each sequence may be millions of bases long and there may be thousands of such sequences which we wish to compare, so not all sequences may fit into main memory at the same time. Each sequence needs to be compared with every other sequence, so we Read More

Many algorithms have been proposed to predict missing links in a variety of real networks. Emphasis is put on raising both accuracy and efficiency of these algorithms. However, less attention is paid to their robustness against either noise or irrationality of a link which exists in almost all of real networks. In this paper, we investigate the robustness of several typical node-similarity-based algorithms and find that these algorithms Read More

In this paper, we aim at predicting protein structural classes for low-homology data sets based on predicted secondary structures. We propose a new and simple kernel method, named as SSEAKSVM, to predict protein structural classes. The secondary structures of all protein sequences are obtained by using the tool PSIPRED and then a linear kernel on the basis of secondary structure element alignment scores is constructed Read More

Protein-protein interactions are critically dependent on just a few residues (“hot spots”) at the interfaces. Hot spots make a dominant contribution to the binding free energy and if mutated they can disrupt the interaction. As mutagenesis studies require significant experimental efforts, there exists a need for accurate and reliable computational hot spot prediction methods. Compared to the supervised hot spot prediction algo Read More

Pseudoknot is an important motif in RNA secondary structure. Early researchers of RNA secondary structure prediction ignored pseudoknots, but now pseudoknot is in focus in RNA secondary structure prediction. Several algorithms like dynamic programming, comparative algorithms, heuristic algorithms, formal grammar algorithms etc have so far been used for pseudoknot prediction, but the prediction of arbitrary pseudoknot Read More

Most food and beverages contain artificial flavor compounds. Creation of artificial flavors is not an easy step and it is hardly ever completely effective. In this paper, we introduce an in silico method in optimization of microbial strains of flavor compound synthesis. Previously, several algorithms exist such as Genetic Algorithm, Evolutionary Algorithm, Opt Knock tool and other related techniques which are widely used t Read More

Advances in ‘omics’ high-throughput technologies have led to a vast amount and quality of available biological data. It has fostered the development of bioinformatics methods to interpret these data. In this regard, characterization of cellular metabolism is a useful task to understand the phenotypic capabilities of an organism. Several in silico approaches have emerged for analysis of metabolic pathways, i Read More

Background: High-throughput protein-protein interaction (PPI) datasets make it possible to exploit the interaction relationship between proteins to predict functions for those proteins that are still functionally unannotated. Although the clustering based approach has proved to be one of effective methods in some cases for protein function prediction, in most cases the prediction results are unsatisfactory. How to define a better si Read More

Technological advancements in high throughput sequencing have led to a tremendous increase in the amount of genomic data produced. With the cost being down to 2,000 USD for a single human genome, sequencing dozens of individuals is an undertaking that is feasible even for a smaller projects or organizations established. However, generating the sequence is only one issue; another one is storing, managing, and analyz Read More

Microbial fuel cells are electrochemical energy systems that transform the organic substrates for bioelectricity generation using the immense catalytic potential of the electrigens. Quinoprotein glucose dehydrogenase of Gluconobacter plays a key role in the oxidation of glucose in MFC’s. The structure of the Quinoprotein glucose dehydrogenase of Gluconobacter suboxydans is still unexplored. Herein, the modeled structur Read More

Protein subcellular localization is closely related to protein functions. Protein can work only in specific subcellular positions, so protein localization in a cell is very important in studies on cytobiology, proteomics, and drug design. Protein subcellular localization prediction based on machine learning is timely and has generated great interest in the field of bioinformatics. This paper reviews the research status of this problem in recent Read More

MicroRNAs (miRNAs) are short non-coding RNAs known to be involved in the gene regulatory functions in human. Major histocompatibility complex (MHC) located on the short arm of chromosome 6 remains as one of the most important regions associated with several human diseases. The complex spans ~4 Mb and covers >120 expressed genes. Gene expression at transcriptional and post transcriptional level is modulated Read More

An important application of microarray technology is the assignment of new subjects to known clinical groups (class prediction), but the huge number of screened genes and the small number of samples make this task difficult. To overcome this problem, the usual approach has been to extract a small subset of significant genes (gene selection) or to use the whole set of genes to build latent components (dimension redu Read More