Ganesan Pugalenthi

发表

GenDiS: Genomic Distribution of protein structural domain Superfamilies

Ramanathan Sowdhamini, Ganesan Pugalenthi, Anirban Bhaduri, 2004, Nucleic Acids Res..

An approach for classification of highly imbalanced data using weighting and undersampling

P. N. Suganthan, Gary B. Fogel, Ashish Anand, 2010, Amino Acids.

MegaMotifBase: a database of structural motifs in protein families and superfamilies

Ponnuthurai N. Suganthan, Ramanathan Sowdhamini, Ganesan Pugalenthi, 2008, Nucleic Acids Res..

DDBASE2.0: updated domain database with improved identification of structural domains

Jiye Shi, Ramanathan Sowdhamini, Tom L. Blundell, 2003, Bioinform..

Bioinformatics and Biology Insights

Ponnuthurai N. Suganthan, Ramanathan Sowdhamini, Khader Shameer, 2022 .

Identification of structurally conserved residues of proteins in absence of structural homologs using neural network ensemble

Ponnuthurai N. Suganthan, Ganesan Pugalenthi, E. Ke Tang, 2008, Bioinform..

HARMONY: a server for the assessment of protein structures

Narayanaswamy Srinivasan, Khader Shameer, Ramanathan Sowdhamini, 2006, Nucleic Acids Res..

iMOT: an interactive package for the selection of spatially interacting motifs

Ramanathan Sowdhamini, Nitin Gupta, Ganesan Pugalenthi, 2004, Nucleic Acids Res..

3dswap-pred: prediction of 3D domain swapping from protein sequence using Random Forest approach.

Ramanathan Sowdhamini, Khader Shameer, Ganesan Pugalenthi, 2011, Protein and peptide letters.

iMOTdb—a comprehensive collection of spatially interacting motifs in proteins

Ramanathan Sowdhamini, Ganesan Pugalenthi, Anirban Bhaduri, 2006, Nucleic Acids Res..

SDBASE: a consortium of native and modelled disulphide bonds in proteins

Ramanathan Sowdhamini, Ganesan Pugalenthi, A. Vinayagam, 2004, Nucleic Acids Res..

BLProt: prediction of bioluminescent proteins based on support vector machine and relieff feature selection

Thomas Martinetz, Ganesan Pugalenthi, Mehrnaz Khodam Hazrati, 2011, BMC Bioinformatics.

Identification and analysis of transcription factor family-specific features derived from DNA and protein information

Ponnuthurai N. Suganthan, Gary B. Fogel, Ashish Anand, 2010, Pattern Recognit. Lett..

3DSwap: curated knowledgebase of proteins involved in 3D domain swapping

Khader Shameer, Ramanathan Sowdhamini, Prashant Shingate, 2011, Database J. Biol. Databases Curation.

SSToSS - Sequence-Structural Templates of Single-Member Superfamilies

Ramanathan Sowdhamini, Ganesan Pugalenthi, Saikat Chakrabarti, 2006, Silico Biol..

A machine learning approach for the identification of odorant binding proteins from sequence-derived properties

Ponnuthurai N. Suganthan, Ramanathan Sowdhamini, Ganesan Pugalenthi, 2007, BMC Bioinformatics.

DIAL: a web-based server for the automatic identification of structural domains in proteins

Ramanathan Sowdhamini, Ganesan Pugalenthi, Govindaraju Archunan, 2005, Nucleic Acids Res..

SMotif: a server for structural motifs in proteins

Ponnuthurai N. Suganthan, Ramanathan Sowdhamini, Ganesan Pugalenthi, 2007, Bioinform..

Prediction of Transcription Factor Families Using DNA Sequence Features

Ponnuthurai N. Suganthan, Gary B. Fogel, Ashish Anand, 2008, PRIB.

SCANMOT: searching for similar sequences using a simultaneous scan of multiple sequence motifs

Ramanathan Sowdhamini, Nitin Bhardwaj, Ganesan Pugalenthi, 2005, Nucleic Acids Res..

BMC Bioinformatics BioMed Central Database

Ramanathan Sowdhamini, Ganesan Pugalenthi, Anirban Bhaduri, 2004 .

Predicting protein structural class by SVM with class-wise optimized features and decision probabilities.

Ganesan Pugalenthi, Ashish Anand, P N Suganthan, 2008, Journal of theoretical biology.

DNA-Prot: Identification of DNA Binding Proteins from Protein Sequence Information using Random Forest

P. N. Suganthan, Ganesan Pugalenthi, P. Suganthan, 2009, Journal of biomolecular structure & dynamics.

Prediction of apoptosis protein locations with genetic algorithms and support vector machines through a new mode of pseudo amino acid composition.

Thomas Martinetz, Ganesan Pugalenthi, P N Suganthan, 2010, Protein and peptide letters.

RSARF: prediction of residue solvent accessibility from protein sequence using random forest method.

Kuo-Chen Chou, Ganesan Pugalenthi, Krishna Kumar Kandaswamy, 2012, Protein and peptide letters.

SVMCRYS: an SVM approach for the prediction of protein crystallization propensity from protein sequence.

Ganesan Pugalenthi, P N Suganthan, Krishna Kumar Kandaswamy, 2010, Protein and peptide letters.

Identification of functionally diverse lipocalin proteins from sequence information using support vector machine

P. N. Suganthan, Ganesan Pugalenthi, Krishna Kumar Kandaswamy, 2010, Amino Acids.

EcmPred: prediction of extracellular matrix proteins based on random forest with maximum relevance minimum redundancy feature selection.

Thomas Martinetz, Ganesan Pugalenthi, Krishna Kumar Kandaswamy, 2013, Journal of theoretical biology.