Improved gene prediction by principal component analysis based autoregressive Yule-Walker method.

Spectral analysis using Fourier techniques is popular with gene prediction because of its simplicity. Model-based autoregressive (AR) spectral estimation gives better resolution even for small DNA segments but selection of appropriate model order is a critical issue. In this article a technique has been proposed where Yule-Walker autoregressive (YW-AR) process is combined with principal component analysis (PCA) for reduction in dimensionality. The spectral peaks of DNA signal are used to detect protein-coding regions based on the 1/3 frequency component. Here optimal model order selection is no more critical as noise is removed by PCA prior to power spectral density (PSD) estimation. Eigenvalue-ratio is used to find the threshold between signal and noise subspaces for data reduction. Superiority of proposed method over fast Fourier Transform (FFT) method and autoregressive method combined with wavelet packet transform (WPT) is established with the help of receiver operating characteristics (ROC) and discrimination measure (DM) respectively.

Effective gene prediction by high resolution frequency estimator based on least-norm solution technique.

Linear algebraic concept of subspace plays a significant role in the recent techniques of spectrum estimation. In this article, the authors have utilized the noise subspace concept for finding hidden periodicities in DNA sequence. With the vast growth of genomic sequences, the demand to identify accurately the protein-coding regions in DNA is increasingly rising. Several techniques of DNA feature extraction which involves various cross fields have come up in the recent past, among which application of digital signal processing tools is of prime importance. It is known that coding segments have a 3-base periodicity, while non-coding regions do not have this unique feature. One of the most important spectrum analysis techniques based on the concept of subspace is the least-norm method. The least-norm estimator developed in this paper shows sharp period-3 peaks in coding regions completely eliminating background noise. Comparison of proposed method with existing sliding discrete Fourier transform (SDFT) method popularly known as modified periodogram method has been drawn on several genes from various organisms and the results show that the proposed method has better as well as an effective approach towards gene prediction. Resolution, quality factor, sensitivity, specificity, miss rate, and wrong rate are used to establish superiority of least-norm gene prediction method over existing method.

Gender preference and awareness regarding sex determination among antenatal mothers attending a medical college of eastern India.

AIM: There are many women "missing" due to an unfavourable sex ratio in India, which has strong patriarchal norms and a preference for sons. Female gender discrimination has been reported in health care, nutrition, education, and resource allocation due to man-made norms, religious beliefs, and recently by ultrasonography resulting in lowered sex ratio. METHODS: The present study attempts to find out the level of awareness regarding sex determination and to explore preference of gender and factors associated among antenatal mothers attending a medical college in eastern India. Interviews were done by predesigned pretested proforma over 6 months. The data were analysed by SPSS 16.0 software for proportions with chi-squared tests and binary logistic regression analysis. RESULTS: Most women who were multigravida did not know about contraceptives; 1.8% of mothers knew the sex of the fetus in present pregnancy while another 34.7% expressed willingness; 13.6% knew of a place which could tell sex of the fetus beforehand; 55.6% expressed their preference of sex of the baby for present pregnancy while 50.6% of their husbands had gender preference. Gender preference was significantly high in subjects with: lower socioeconomic status (p=0.011); lower level of education of mother (p=0.047) and husband (p=0.0001); multigravida (p=0.002); presence of living children (p=0.0001); and husband having preference of sex of baby (p=0.0001). CONCLUSIONS: Parental education, socioeconomic background, and number of living issues were the main predictors for gender preference. Awareness regarding gender preference and related law and parental counselling to avoid gender preference with adoption of small family norm is recommended.

Parasitosis: a study among Nepali children in the district of Darjeeling.

A cross-sectional study carried out among 370 school-going children of the Nepali community, aged 5-10 years, in the Siliguri subdivision of Darjeeling district revealed the prevalence of parasitic infestation to be 51.4 per cent of which 28.2% and 23.2% had single and multiple parasitism respectively. In the group of single parasitism, A. lumbricoides was the commonest infestation (31.73%) and in multiple parasitisms, A. lumbricoides and T. Trichiura combination was found to be the most prevalent (36.05%). A significant statistical association was observed in the decrease of worm infestation rate among children with the increasing educational status of their mothers. The study also revealed that 19.73% and 18.91% of the mothers had no knowledge about mode of transmission and prevention of worm infestation respectively.