International Journal of Bioinformatics Research and Applications (8 papers in press)

• A Parallel Combinatorial Algorithm for Subtle Motifs
  by Srinivasulu Uyyala 
  Abstract: In Bioinformatics, Motif Finding is one of the most popular problems which have many applications. Generally motif finding is to locate recurring patterns in the sequence of nucleotides or amino acids. The main difficulty of the problem is that the patterns are not exact matches due to biological mutations. This has been proven to be NP-complete. In the literature, a famous approximated problem known as the Challenge Problem has been provided many solutions. Nevertheless, they don't address certain subtleties. Among them one is addressed by Y. Hu (2003). To the best of our knowledge, there is no parallel equivalent for Hu's solution and hence we propose a parallel combinatorial algorithm for subtle motif finding on a Shared Memory Multiprocessor model, in this paper. At the end, we suggest a method of implementation for the same.
  Keywords: Motif Finding, Subtle Motifs, combinatorics, parallel algorithm, EREW PRAM model, Distributed Shared memory.
   
• Algorithm for Thermodynamically Based Prediction of DNA/DNA Cross-hybridisation
  by Svetlana Torgasin, Karl-Heinz Zimmermann 
  Abstract: A careful design of DNA strands is crucial for several biological applications such as microarray techniques, polymerase chain reaction (PCR), and DNA computing. For this, the important criterion under laboratory conditions is the hybridisation energy of two DNA strands. During the last decade, a thermodynamic model was developed that allows to calculate the DNA/DNA hybridisation energy and recently also the cross-hybridisation energy of structural motifs. For the prediction of the DNA/DNA cross-hybridisation energy, the corresponding RNA folding algorithms are usually applied. However, the specifics of DNA necessitates the development of separate DNA/DNA pairing algorithms. A new algorithm for the secondary structure prediction of DNA/DNA cross-hybridisation complexes called HybGraph is introduced. The method is based on Gibbs free energy minimisation and employs the paradigm of dynamic programming.
  Keywords: DNA hybridisation; dynamic programming; Gibbs free energy; nearest neighbour model; DNA structural motifs
   
• Stability of RNA structural motifs and its influence on editing efficiency by adenosine deaminases
  by Vinhthuy Phan, Allen Thomas, Kriangsiri Malasri, Carrie Hayes Sutter 
  Abstract: We propose a novel method to estimate editing efficiency by adenosine deaminases that act on RNA (ADARs). The method employs the notion of stability of secondary structure in the vicinity of edited sites during transcription. Such an analysis of “dynamic” structural motifs of RNA is important because as a pre-spliced RNA is being transcribed and elongated, its entire structure, and thus its local structures, may change drastically. Our simulation showed that the stability of structures in the vicinity of edited sites correlates moderately highly with editing efficiency of edited sites recently established in laboratory experiments.
  Keywords: RNA Editing; ADAR; RNA Motif; Structural Motif; Dynamic Motif; Edited Site Prediction
   
• A Text-Mining Technique for Extracting Gene-Disease Associations from the Biomedical Literature
  by Hisham Al-Mubaid 
  Abstract: We propose a new text mining technique to identify associations between biological entities, specifically genes–diseases associations, from the biomedical literature. The proposed method is simple and straightforward; it uses two sets (a positive set and a negative set) of documents and utilizes the concepts of expectation (ex), evidence (ev), and Z-scores in combining positive and negative evidences in determining the significant gene-disease associations from Medline documents. Moreover, the method offers an efficient way to handle gene names, aliases, symbols, and abbreviations. We evaluated the method in discovering gene-to-disease associations from literature and the experimental results are impressive. We verified our results and confirmed the effectiveness of the proposed technique by various ways. For example, we ran the technique on some discovered and known genes-diseases relationships. Our method was able to discover associations between genes and various diseases like Amyotrophic lateral sclerosis, Tuberous Sclerosis, Autism, Homocystinuria, Bipolar Disorder, Atherosclerosis and more.
  Keywords: Gene-disease associations, Biomedical knowledge discovery, Biomedical information extraction, Text mining, Mining biomedical literature, Bioinformatics.
   
• MEGA Biocentric Software for Sequence and Phylogenetic Analysis: A Review
  by Vipan sohpal, Apurba Dey, Amarpal Singh 
  Abstract: Bio-computing has moved into central position in molecular biology research. Enormous improvements in genetic mapping and sequencing technology have led to the accumulation of vast amount of biological information in the database. With the advent of this extensive repertoire of raw sequence information, the next major challenge for a modern researcher is to interpret this biological information. Molecular Evolutionary Genetic Analysis (MEGA) is bio-computational software to fills the vacuum between data development and analysis. It works in automated manner with minimum amount of operational complexity for user. In this paper an attempt to review the evolution of MEGA software from MEGA1 to MEGA 4 for its working and application. Moreover the Data analysis, implementation and advantages over other bioinformatics software have been discussed systematically.
  Keywords: Biocomputing, Molecular Biology, Bioinformatics Software, Alignment and MEGA
   
• A More elaborative way to check codon quality : an open source program.
  by Rakesh Shardiwal, Sohrab Sayed 
  Abstract: Relative Synonymous Codons Uses and Relative Adaptiveness of a Codon table bias importance in gene expression are well documented in the literature. However, to improve the gene expression we need to figure out which codons are optimal for the expression in order to synthesize an appropriate DNA sequence. An alternative to the manual approach, which is obviously a tedious task, is to set up software on your computer to perform this. Though such kinds of programs are available on the internet, none of them are open-source libraries. Here you can use our perl program to do your task more easily and efficiently. It's free for everyone.
  Keywords: Relative Synonymous Codons, Relative Adaptiveness of a Codon, Bioinformatics, Perl, Bioperl, Codons, expression analysis
   
• Characterization of Simple Sequence Repeats from Human ESTs and Creation of a Comprehensive Data Base
  by Amit kumar 
  Abstract: The aim of the present analysis is to create a complete database of Simple Sequence Repeats (SSRs) occurring in the Expressed Sequence Tags (ESTs) of Human Genome. For the recognition of SSRs, various Bioinformatics Tools, Databases and Softwares are employed. The data are analyzed statistically for Mean, Density and Frequency distribution of the identified Repeats. A consolidated Database is created and maintained in SAS Environment. This database can provide comprehensive information regarding (1) the complete sequence of Microsatellites/Tandem repeats, (2) the number of times each one is repeated, (3) the starting and ending position of each repeat, and (4) its length. In addition the database can also provide the location of the gene and also its function. As these Microsatellites are known to be widely used in a variety of fundamental and applied fields of life and medical sciences, the availability and accessibility to such comprehensive data base would greatly help the researchers.
  Keywords: Biomarkers, EST, Expressed sequence tags, Statistical analysis, Single sequence repeats, DNA microarrays, differential expression analysis, biological database, SAS, microsatellites, bioinformatics tools, Human genome
   
• Distinct role of non-covalent interactions to the function and structural stability of Glutaredoxins: a multifunctional redox protein
  by Rao Madhavan 
  Abstract: In the present work, the role of cation-л and CH…л interactions in the activity of glutaredoxins is analyzed. Among the proteins, an average of 1 cation-л interaction per 109 residues and an average of 1 CH…л interaction per 16 residues were found. These interactions were influenced by long range contacts whereas short and medium range contacts were found insignificant. Significant differences in these interactions were noticed when the same glutaredoxin was analyzed in its glutathionylated, reduced and oxidized states. Since activities of glutaredoxins depend on its state, the role of these interactions in regulation of these proteins might be significant.
  Keywords: Glutaredoxins, Cation-л interaction, CH…л interaction, Long range contacts