Indian Agricultural Statistics Research Institute

About: Indian Agricultural Statistics Research Institute is a facility organization based out in New Delhi, India. It is known for research contribution in the topics: Population & Small area estimation. The organization has 454 authors who have published 870 publications receiving 7987 citations.

DIRProt: a computational approach for discriminating insecticide resistant proteins from non-resistant proteins.

Abstract: Insecticide resistance is a major challenge for the control program of insect pests in the fields of crop protection, human and animal health etc. Resistance to different insecticides is conferred by the proteins encoded from certain class of genes of the insects. To distinguish the insecticide resistant proteins from non-resistant proteins, no computational tool is available till date. Thus, development of such a computational tool will be helpful in predicting the insecticide resistant proteins, which can be targeted for developing appropriate insecticides. Five different sets of feature viz., amino acid composition (AAC), di-peptide composition (DPC), pseudo amino acid composition (PAAC), composition-transition-distribution (CTD) and auto-correlation function (ACF) were used to map the protein sequences into numeric feature vectors. The encoded numeric vectors were then used as input in support vector machine (SVM) for classification of insecticide resistant and non-resistant proteins. Higher accuracies were obtained under RBF kernel than that of other kernels. Further, accuracies were observed to be higher for DPC feature set as compared to others. The proposed approach achieved an overall accuracy of >90% in discriminating resistant from non-resistant proteins. Further, the two classes of resistant proteins i.e., detoxification-based and target-based were discriminated from non-resistant proteins with >95% accuracy. Besides, >95% accuracy was also observed for discrimination of proteins involved in detoxification- and target-based resistance mechanisms. The proposed approach not only outperformed Blastp, PSI-Blast and Delta-Blast algorithms, but also achieved >92% accuracy while assessed using an independent dataset of 75 insecticide resistant proteins. This paper presents the first computational approach for discriminating the insecticide resistant proteins from non-resistant proteins. Based on the proposed approach, an online prediction server DIRProt has also been developed for computational prediction of insecticide resistant proteins, which is accessible at http://cabgrid.res.in:8080/dirprot/ . The proposed approach is believed to supplement the efforts needed to develop dynamic insecticides in wet-lab by targeting the insecticide resistant proteins.

District-wise trend analysis of rainfall pattern in last century (1901-2000) over Gangetic region in West Bengal, India

Abstract: The aim of the present study was to estimate long-term trend in the amount of rainfall for Gangetic West Bengal (GWB) meteorological sub-division of India and each of the 13 districts under GWB separately. Monthly rainfall time series data of 100 years (1901-2000) were analyzed to measure monotonous trend of rainfall employing Sen’s slope estimator. Statistical significance of the trend was determined using non-parametric Mann-Kendall test. An important result derived from the analysis was that the GWB sub-division and South 24 Parganas (S24P) district showed significant increasing trend (mm/year) of annual rainfall measuring 2.025 and 4.99 respectively. An inclining trend of monsoon precipitation, which was significant, found in four districts viz. Bankura, North 24 Parganas (N24P), S24P and West Midnapore along with GWB itself. A major finding of the study revealed that six districts and GWB had significant increasing trend in September rainfall with a maximum value of 1.324 mm/year in S24P district. Contribution of rainfall in October and post-monsoon season as well increased considerably in Kolkata and S24P districts while in December, similar trend was observed for Birbhum and Howrah districts. Murshidabad, S24P and East Midnapore districts experienced significant rising trend of precipitation in July, August and November respectively. On the contrary, Burdwan and Nadia districts, in the month of May and pre-monsoon season, had considerable declining trend of rainfall. Significant decreasing trend (mm/year) of precipitation, a concern for Nadia district, with magnitude of 0.127 and 0.293, was observed in the months of March and April respectively.

Standardizing Proteomics Workflow for Liquid Chromatography-Mass Spectrometry: Technical and Statistical Considerations.

Abstract: Introduction: The quantitative measurements based on liquid chromatography (LC) coupled with mass spectrometry (MS) often suffer from the problem of missing values and data heterogeneity from technical variability. We considered a proteomics data set generated from human kidney biopsy material to investigate the technical effects of sample preparation and the quantitative MS. Methods: We studied the effect of tissue storage methods (TSMs) and tissue extraction methods (TEMs) on data analysis. There are two TSMs: frozen (FR) and FFPE (formalin-fixed paraffin embedded); and three TEMs: MAX, TX followed by MAX and SDS followed by MAX. We assessed the impact of different strategies to analyze the data while considering heterogeneity and MVs. We have used analysis of variance (ANOVA) model to study the effects due to various sources of variability. Results and Conclusion: We found that the FFPE TSM is better than the FR TSM. We also found that the one-step TEM (MAX) is better than those of two-steps TEMs. Furthermore, we found the imputation method is a better approach than excluding the proteins with MVs or using unbalanced design.