An Application of Logistic Regression and Multifactor Dimensionality Reduction Analyses for Detecting Genotype-Phenotype Interactions Associated with Developing of Atherosclerosis in Bulgarian Cohort

A novel β-fructofuranosidase produced by Penicillium citreonigrum URM 4459: purification and biochemical features

Fructooligosaccharides (FOS) are prebiotics of interest to the food industry. These compounds can be produced through the transfructosylation reaction by the enzyme fructofuranosidase. This enzyme is widely produced by fungi in a medium rich in sugar. Therefore, in this work, the main objectives were production, purification, biochemical characterization of a novel fructofuranosidase enzyme by Penicillium citreonigrum URM 4459 and synthesize and evaluate the antibacterial potential of fructooligosaccharides. With respect to sucrose hydrolysis, the optimal pH was 5.5, the apparent Km for purified FFase was 3.8 mM, the molecular mass was 43.0 kDa, estimated by gel filtration on Superdex increase G75 controlled by AKTA Avant 25 and confirmed by 10% SDS-PAGE under denaturing condition. Also, the isoelectric point was 4.9. The fractions obtained with enzymatic activities, both stable at acidic pH and high temperatures, as well as being able to produce FOS. Regarding antibacterial activity, the FOS produced in this study showed better results than commercial FOS and other carbon sources. Thus, this work presents relevant data for the use of P. citreonigum to produce fructofuranosidase and consequently FOS and can be used in the food and pharmaceutical industry.

HS-MMGKG: A Fast Multi-objective Harmony Search Algorithm for Two-locus Model Detection in GWAS

Background::

Genome-Wide Association Study (GWAS) plays a very important role in identifying the causes of a disease. Because most of the existing methods for genetic-interaction detection in GWAS are designed for a single-correlation model, their performances vary considerably for different disease models. These methods usually have high computation cost and low accuracy.

Method::

We present a new multi-objective heuristic optimization methodology named HSMMGKG for detecting genetic interactions. In HS-MMGKG, we use harmony search with five objective functions to improve the efficiency and accuracy. A new strategy based on p-value and MDR is adopted to generate more reasonable results. The Boolean representation in BOOST is modified to calculate the five functions rapidly. These strategies take less time complexity and have higher accuracy while detecting the potential models.

Results::

We compared HS-MMGKG with CSE, MACOED and FHSA-SED using 26 simulated datasets. The experimental results demonstrate that our method outperforms others in accuracy and computation time. Our method has identified many two-locus SNP combinations that are associated with seven diseases in WTCCC dataset. Some of the SNPs have direct evidence in CTD database. The results may be helpful to further explain the pathogenesis.

Conclusion::

It is anticipated that our proposed algorithm could be used in GWAS which is helpful in understanding disease mechanism, diagnosis and prognosis.