N. Hemalatha

发表

A Machine Learning Approach for Prediction of Gibberellic Acid Metabolic Enzymes in Monocotyledonous Plants

M. K. Rajesh, P. Sreepriya, S. Naganeeswaran, 2014 .

Machine Learning Approaches for Prediction of Expansin Gene Family in Indica Rice

M. K. Rajesh, N. Narayanan, N. Hemalatha, 2013, Agricultural Research.

A machine learning approach for detecting MAP kinase in the genome of Oryza sativa L. ssp. indica

N. K. Narayanan, N. Hemalatha, M. K. Rajesh, 2014, 2014 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology.

Maternal body mass index and feto-maternal outcome: a comparative study

N. Hemalatha, S. ., 2019, International Journal of Reproduction, Contraception, Obstetrics and Gynecology.

A Support Vector Machine Approach for LTP Using Amino Acid Composition

N. Narayanan, N. Hemalatha, 2016 .

Development of a tool for computational prediction of σ70 promoters in Pseudomonas spp using SVM and HMM approaches

M. K. Rajesh, N. Hemalatha, M. Gopal, 2014 .

PRGPred: A platform for prediction of domains of resistance gene analogue (RGA) in Arecaceae developed by using machine learning algorithms

M. K. Rajesh, S. Naganeeswaran, N. Hemalatha, 2015 .

CnMAPKPred : A machine learning approach for predicting mitogen-activated protein kinase in Cocos nucifera

M. K. Rajesh, V. Akhil, N. Hemalatha, 2015 .

INTERNATIONAL JOURNAL OF MANAGEMENT RESEARCH AND REVIEW BUSINESS PROCESS REENGINEERING AND ITS APPLICATIONS

C. S. Ramanigopal, G. Palaniappan, N. Hemalatha, 2012 .

LTTRPred: A tool for prediction of LysR-type transcriptional regulator of pyoluteorin pathway in plant growth promoting Pseudomonas spp.

M. K. Rajesh, N. Hemalatha, Anil Paul, 2014 .

A Machine Learning Approach for Discovery of Novel Non- Ribosomal Peptide Synthetases (NRPS) in genomes of Plant Growth Promoting Pseudomonas Spp

M. K. Rajesh, N. Hemalatha, T. Jamshinath, 2014 .

Machine Learning Approaches for Prediction of Expansin Gene Family in Indica Rice

M. K. Rajesh, N. Narayanan, N. Hemalatha, 2013, Agricultural Research.

Genome-wide analysis and identification of genes related to expansin gene family in indica rice

N. K. Narayanan, N. Hemalatha, M. K. Rajesh, 2011, Int. J. Bioinform. Res. Appl..

Protein Structure and Function Prediction Using Machine Learning Methods - A Review

Siddhant Naik, Jeason Rinton Saldanha, N Hemalatha, 2014 .

Machine Learning Algorithm for Predicting Ethylene Responsive Transcription Factor in Rice Using an Ensemble Classifier

N. Hemalatha, M. K. Rajesh, V. F. Brendon, 2015 .

Genome-Wide Analysis of Putative ERF and DREB GENE Families in Indica Rice (O. sativa L. subsp. Indica)

N Hemalatha, K RajeshM., N K Narayanan, 2012 .

Text Based Smart Answering System in Agriculture using RNN

N. Hemalatha, R. Sukumar, S. Sarin, 2021, ICON.

Teaching aids-perceptions of medical

N. R. Hemalatha, Mamata P. Samaga, N. Hemalatha, 2014 .

Applications of Machine Learning - A Survey

Pradeep, N Hemalatha, Larisa, 2014 .

A Study on Employee Retention Techniques

N. Hemalatha, Dr. A. Savarimuthu, 2013 .

Classification of fruits and vegetables using ResNet model.

N. Hemalatha, R. Sukumar, P. Sukhetha, 2021 .

A Machine Learning Approach for Prediction of Domains of DELLA Proteins, a Key Component of Gibberellic Acid Signaling in Plants

N. Hemalatha, M. K. Rajesh, V. Akhil, 2016 .