RNA-binding proteins (RBPs) are essential for post-transcriptional gene regulation in eukaryotes,... more RNA-binding proteins (RBPs) are essential for post-transcriptional gene regulation in eukaryotes, including splicing control, mRNA transport and decay. Thus, accurate identification of RBPs is important to understand gene expression and regulation of cell state. In order to detect RBPs, a number of computational models have been developed. These methods made use of datasets from several eukaryotic species, specifically from mice and humans. Although some models have been tested on Arabidopsis, these techniques fall short of correctly identifying RBPs for other plant species. Therefore, the development of a powerful computational model for identifying plant-specific RBPs is needed. In this study, we presented a novel computational model for locating RBPs in plants. Five deep learning models and ten shallow learning algorithms were utilized for prediction with 20 sequence-derived and 20 evolutionary feature sets. The highest repeated five-fold cross-validation accuracy, 91.24% AU-ROC ...
Influence of weather variables on occurrence of spiders in pigeon pea across locations of seven a... more Influence of weather variables on occurrence of spiders in pigeon pea across locations of seven agro-climatic zones of India was studied in addition to development of forecast models with their comparisons on performance. Considering the non-normal and nonlinear nature of time series data of spiders, non-parametric techniques were applied with developed algorithm based on combinations of wavelet–regression and wavelet–artificial neural network (ANN) models. Haar wavelet filter decomposed each of the series to extract the actual signal from the noisy data. Prediction accuracy of developed models, viz., multiple regression, wavelet–regression, and wavelet–ANN, tested using root mean square error (RMSE) and mean absolute percentage error (MAPE), indicated better performance of wavelet–ANN model. Diebold Mariano (DM) test also confirmed that the prediction accuracy of wavelet–ANN model, and hence its use to forecast spiders in conjunction with the values of pest–defender ratios, would n...
MicroRNAs (miRNAs) play a significant role in plant response to different abiotic stresses. Thus,... more MicroRNAs (miRNAs) play a significant role in plant response to different abiotic stresses. Thus, identification of abiotic stress-responsive miRNAs holds immense importance in crop breeding programmes to develop cultivars resistant to abiotic stresses. In this study, we developed a machine learning-based computational method for prediction of miRNAs associated with abiotic stresses. Three types of datasets were used for prediction, i.e., miRNA, Pre-miRNA, and Pre-miRNA + miRNA. The pseudo K-tuple nucleotide compositional features were generated for each sequence to transform the sequence data into numeric feature vectors. Support vector machine (SVM) was employed for prediction. The area under receiver operating characteristics curve (auROC) of 70.21, 69.71, 77.94 and area under precision-recall curve (auPRC) of 69.96, 65.64, 77.32 percentages were obtained for miRNA, Pre-miRNA, and Pre-miRNA + miRNA datasets, respectively. Overall prediction accuracies for the independent test set...
The Indo-gangetic plains (IGP) in India occupies 13 % of the total geographical area and produces... more The Indo-gangetic plains (IGP) in India occupies 13 % of the total geographical area and produces 50 % of total food grain to feed 40 % population of the country. Dynamic CO2FIX model v3.1 has been used to assess the baseline (2011) carbon and to estimate the carbon sequestration potential (CSP) of agroforestry systems (AFS) for a simulation period of 30 years in three districts viz. Ludhiana (upper IGP in Punjab), Sultanpur (middle IGP in Uttar Pradesh) and Uttar Dinajpur (lower IGP in West Bengal) respectively. The estimated numbers of trees existing in farmer's field on per hectare basis in these districts were 37.95, 6.14 and 6.20, respectively. The baseline standing biomass in the tree components varied from 2.45 to 2.88 Mg DM ha -1 and the total biomass (tree ? crop) from 11.14 to 25.97 Mg DM ha -1 in the three districts. The soil organic carbon in the baseline ranged from 8.13 to 9.12 Mg C ha -1 and is expected to increase from 8.63 to 24.51 Mg C ha -1 . The CSP of existing AFS (for 30 years simulation) has been estimated to the tune of 0.111, 0.126 and 0.551 Mg C ha -1 year -1 for Sultanpur, Dinajpur and Ludhiana districts, respectively. CSP of AFS increases with increasing tree density per hectare. Site specific climatic parameters like monthly temperature, annual precipitation and evapotranspiration also moderates the CSP of AFS. The preliminary estimates of the area under AFS's were 2.06 % (3,256 ha), 2.08 % (6,440 ha) and 12.69 % (38,860 ha) in Sultanpur, Dinajpur and Ludhiana respectively.
RNA-binding proteins (RBPs) are essential for post-transcriptional gene regulation in eukaryotes,... more RNA-binding proteins (RBPs) are essential for post-transcriptional gene regulation in eukaryotes, including splicing control, mRNA transport and decay. Thus, accurate identification of RBPs is important to understand gene expression and regulation of cell state. In order to detect RBPs, a number of computational models have been developed. These methods made use of datasets from several eukaryotic species, specifically from mice and humans. Although some models have been tested on Arabidopsis, these techniques fall short of correctly identifying RBPs for other plant species. Therefore, the development of a powerful computational model for identifying plant-specific RBPs is needed. In this study, we presented a novel computational model for locating RBPs in plants. Five deep learning models and ten shallow learning algorithms were utilized for prediction with 20 sequence-derived and 20 evolutionary feature sets. The highest repeated five-fold cross-validation accuracy, 91.24% AU-ROC ...
Influence of weather variables on occurrence of spiders in pigeon pea across locations of seven a... more Influence of weather variables on occurrence of spiders in pigeon pea across locations of seven agro-climatic zones of India was studied in addition to development of forecast models with their comparisons on performance. Considering the non-normal and nonlinear nature of time series data of spiders, non-parametric techniques were applied with developed algorithm based on combinations of wavelet–regression and wavelet–artificial neural network (ANN) models. Haar wavelet filter decomposed each of the series to extract the actual signal from the noisy data. Prediction accuracy of developed models, viz., multiple regression, wavelet–regression, and wavelet–ANN, tested using root mean square error (RMSE) and mean absolute percentage error (MAPE), indicated better performance of wavelet–ANN model. Diebold Mariano (DM) test also confirmed that the prediction accuracy of wavelet–ANN model, and hence its use to forecast spiders in conjunction with the values of pest–defender ratios, would n...
MicroRNAs (miRNAs) play a significant role in plant response to different abiotic stresses. Thus,... more MicroRNAs (miRNAs) play a significant role in plant response to different abiotic stresses. Thus, identification of abiotic stress-responsive miRNAs holds immense importance in crop breeding programmes to develop cultivars resistant to abiotic stresses. In this study, we developed a machine learning-based computational method for prediction of miRNAs associated with abiotic stresses. Three types of datasets were used for prediction, i.e., miRNA, Pre-miRNA, and Pre-miRNA + miRNA. The pseudo K-tuple nucleotide compositional features were generated for each sequence to transform the sequence data into numeric feature vectors. Support vector machine (SVM) was employed for prediction. The area under receiver operating characteristics curve (auROC) of 70.21, 69.71, 77.94 and area under precision-recall curve (auPRC) of 69.96, 65.64, 77.32 percentages were obtained for miRNA, Pre-miRNA, and Pre-miRNA + miRNA datasets, respectively. Overall prediction accuracies for the independent test set...
The Indo-gangetic plains (IGP) in India occupies 13 % of the total geographical area and produces... more The Indo-gangetic plains (IGP) in India occupies 13 % of the total geographical area and produces 50 % of total food grain to feed 40 % population of the country. Dynamic CO2FIX model v3.1 has been used to assess the baseline (2011) carbon and to estimate the carbon sequestration potential (CSP) of agroforestry systems (AFS) for a simulation period of 30 years in three districts viz. Ludhiana (upper IGP in Punjab), Sultanpur (middle IGP in Uttar Pradesh) and Uttar Dinajpur (lower IGP in West Bengal) respectively. The estimated numbers of trees existing in farmer's field on per hectare basis in these districts were 37.95, 6.14 and 6.20, respectively. The baseline standing biomass in the tree components varied from 2.45 to 2.88 Mg DM ha -1 and the total biomass (tree ? crop) from 11.14 to 25.97 Mg DM ha -1 in the three districts. The soil organic carbon in the baseline ranged from 8.13 to 9.12 Mg C ha -1 and is expected to increase from 8.63 to 24.51 Mg C ha -1 . The CSP of existing AFS (for 30 years simulation) has been estimated to the tune of 0.111, 0.126 and 0.551 Mg C ha -1 year -1 for Sultanpur, Dinajpur and Ludhiana districts, respectively. CSP of AFS increases with increasing tree density per hectare. Site specific climatic parameters like monthly temperature, annual precipitation and evapotranspiration also moderates the CSP of AFS. The preliminary estimates of the area under AFS's were 2.06 % (3,256 ha), 2.08 % (6,440 ha) and 12.69 % (38,860 ha) in Sultanpur, Dinajpur and Ludhiana respectively.
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Papers by Ajit Gupta