Heritage Institute of Technology

About: Heritage Institute of Technology is a based out in . It is known for research contribution in the topics: Support vector machine & Transconductance. The organization has 581 authors who have published 1045 publications receiving 8345 citations.

An Improved Fuzzy Based Missing Value Estimation in DNA Microarray Validated by Gene Ranking

Abstract: Most of the gene expression data analysis algorithms require the entire gene expression matrix without any missing values. Hence, it is necessary to devise methods which would impute missing data values accurately. There exist a number of imputation algorithms to estimate those missing values. This work starts with a microarray dataset containing multiple missing values. We first apply the modified version of the fuzzy theory based existing method LRFDVImpute to impute multiple missing values of time series gene expression data and then validate the result of imputation by genetic algorithm GA based gene ranking methodology along with some regular statistical validation techniques, like RMSE method. Gene ranking, as far as our knowledge, has not been used yet to validate the result of missing value estimation. Firstly, the proposed method has been tested on the very popular Spellman dataset and results show that error margins have been drastically reduced compared to some previous works, which indirectly validates the statistical significance of the proposed method. Then it has been applied on four other 2-class benchmark datasets, like Colorectal Cancer tumours dataset GDS4382, Breast Cancer dataset GSE349-350, Prostate Cancer dataset, and DLBCL-FL Leukaemia for both missing value estimation and ranking the genes, and the results show that the proposed method can reach 100% classification accuracy with very few dominant genes, which indirectly validates the biological significance of the proposed method.

Synthesis, Characterization and Performance Evaluation of a Solid Acid Catalyst Prepared from Coconut Shell for Hydrolyzing Pretreated Acacia nilotica Heartwood

Abstract: The present investigation aims to develop a solid acid-type heterogeneous catalyst for the hydrolysis of biomass using coconut shell, an inexpensive and easily available material, as yet unexplored in this field. Catalyst characterization by scanning electron micrography, X-ray diffraction, FTIR spectroscopy and nitrogen adsorption has been carried out. Pretreated sawdust from Acacia nilotica heartwood and microcrystalline cellulose were hydrolyzed in aqueous medium using the developed catalyst. Maximum sugar yields of 91% and 93% were obtained on hydrolysis of pretreated sawdust and microcrystalline cellulose, respectively. The principal hydrolysis product was glucose with a selectivity of 98%. These results highlight the potential of the developed catalyst for use in industrial biomass saccharification.