2008 |
37 | EE | M. Michael Gromiha,
Shandar Ahmad,
Makiko Suwa:
Neural network based prediction of protein structure and Function: Comparison with other machine learning methods.
IJCNN 2008: 1739-1744 |
36 | EE | Y.-h. Taguchi,
M. Michael Gromiha:
Gene Ontology term prediction based upon amino acid occurrence.
IJCNN 2008: 615-620 |
35 | EE | M. Michael Gromiha,
Liang-Tsung Huang,
Lien Fu Lai:
Sequence Based Prediction of Protein Mutant Stability and Discrimination of Thermophilic Proteins.
PRIB 2008: 1-12 |
34 | EE | Yu-Yen Ou,
M. Michael Gromiha,
Shu-An Chen,
Makiko Suwa:
TMBETADISC-RBF: Discrimination of beta-barrel membrane proteins using RBF networks and PSSM profiles.
Computational Biology and Chemistry 32(3): 227-231 (2008) |
33 | EE | Liang-Tsung Huang,
M. Michael Gromiha:
Analysis and prediction of protein folding rates using quadratic response surface models.
Journal of Computational Chemistry 29(10): 1675-1683 (2008) |
2007 |
32 | EE | Y.-h. Taguchi,
M. Michael Gromiha:
Protein Fold Recognition Based Upon the Amino Acid Occurrence.
PRIB 2007: 120-131 |
31 | EE | M. Michael Gromiha:
Bioinformatics on beta-Barrel Membrane Proteins: Sequence and Structural Analysis, Discrimination and Prediction.
PRIB 2007: 148-157 |
30 | EE | Liang-Tsung Huang,
M. Michael Gromiha,
Shinn-Ying Ho:
iPTREE-STAB: interpretable decision tree based method for predicting protein stability changes upon mutations.
Bioinformatics 23(10): 1292-1293 (2007) |
29 | EE | M. Michael Gromiha,
Yukimitsu Yabuki,
Srinesh Kundu,
Sivasundaram Suharnan,
Makiko Suwa:
TMBETA-GENOME: database for annotated ß-barrel membrane proteins in genomic sequences.
Nucleic Acids Research 35(Database-Issue): 314-316 (2007) |
2006 |
28 | EE | Liang-Tsung Huang,
M. Michael Gromiha,
Shiow-Fen Hwang,
Shinn-Ying Ho:
Knowledge acquisition and development of accurate rules for predicting protein stability changes.
Computational Biology and Chemistry 30(6): 408-415 (2006) |
27 | EE | M. Michael Gromiha,
Samuel Selvaraj,
A. Mary Thangakani:
A Statistical Method for Predicting Protein Unfolding Rates from Amino Acid Sequence.
Journal of Chemical Information and Modeling 46(3): 1503-1508 (2006) |
26 | EE | M. D. Shaji Kumar,
M. Michael Gromiha:
PINT: Protein-protein Interactions Thermodynamic Database.
Nucleic Acids Research 34(Database-Issue): 195-198 (2006) |
25 | EE | M. D. Shaji Kumar,
K. Abdulla Bava,
M. Michael Gromiha,
Ponraj Prabakaran,
Koji Kitajima,
Hatsuho Uedaira,
Akinori Sarai:
ProTherm and ProNIT: thermodynamic databases for proteins and protein-nucleic acid interactions.
Nucleic Acids Research 34(Database-Issue): 204-206 (2006) |
24 | EE | Vijaya Parthiban,
M. Michael Gromiha,
Dietmar Schomburg:
CUPSAT: prediction of protein stability upon point mutations.
Nucleic Acids Research 34(Web-Server-Issue): 239-242 (2006) |
23 | EE | M. Michael Gromiha,
A. Mary Thangakani,
Samuel Selvaraj:
FOLD-RATE: prediction of protein folding rates from amino acid sequence.
Nucleic Acids Research 34(Web-Server-Issue): 70-74 (2006) |
2005 |
22 | EE | Keun-Joon Park,
M. Michael Gromiha,
Paul Horton,
Makiko Suwa:
Discrimination of outer membrane proteins using support vector machines.
Bioinformatics 21(23): 4223-4229 (2005) |
21 | EE | M. Michael Gromiha,
Makiko Suwa:
A simple statistical method for discriminating outer membrane proteins with better accuracy.
Bioinformatics 21(7): 961-968 (2005) |
20 | EE | K. Saraboji,
M. Michael Gromiha,
Mon Nanjappa Ponnuswamy:
Relative importance of secondary structure and solvent accessibility to the stability of protein mutants.: A case study with amino acid properties and energetics on T4 and human lysozymes.
Computational Biology and Chemistry 29(1): 25-35 (2005) |
19 | EE | M. Michael Gromiha,
Shandar Ahmad,
Makiko Suwa:
Application of residue distribution along the sequence for discriminating outer membrane proteins.
Computational Biology and Chemistry 29(2): 135-142 (2005) |
18 | EE | Akinori Sarai,
Jorg Siebers,
Samuel Selvaraj,
M. Michael Gromiha,
Hidetoshi Kono:
Integration of Bioinformatics and Computational Biology to Understand Protein-dna Recognition Mechanism.
J. Bioinformatics and Computational Biology 3(1): 169-183 (2005) |
17 | EE | M. Michael Gromiha:
A Statistical Model for Predicting Protein Folding Rates from Amino Acid Sequence with Structural Class Information.
Journal of Chemical Information and Modeling 45(2): 494-501 (2005) |
16 | EE | M. Michael Gromiha,
Shandar Ahmad,
Makiko Suwa:
TMBETA-NET: discrimination and prediction of membrane spanning ß-strands in outer membrane proteins.
Nucleic Acids Research 33(Web-Server-Issue): 164-167 (2005) |
15 | EE | Csaba Magyar,
M. Michael Gromiha,
Gerard Pujadas,
Gábor E. Tusnády,
István Simon:
SRide: a server for identifying stabilizing residues in proteins.
Nucleic Acids Research 33(Web-Server-Issue): 303-305 (2005) |
2004 |
14 | EE | Akinori Sarai,
Samuel Selvaraj,
M. Michael Gromiha,
Hidetoshi Kono:
Structure-Function Relationship in DNA Sequence Recognition by Transcription Factors.
APBC 2004: 233-238 |
13 | EE | Shandar Ahmad,
M. Michael Gromiha,
Hamed Fawareh,
Akinori Sarai:
ASAView: Database and tool for solvent accessibility representation in proteins.
BMC Bioinformatics 5: 51 (2004) |
12 | EE | Shandar Ahmad,
M. Michael Gromiha,
Akinori Sarai:
Analysis and prediction of DNA-binding proteins and their binding residues based on composition, sequence and structural information.
Bioinformatics 20(4): (2004) |
11 | EE | M. Michael Gromiha,
Shandar Ahmad,
Makiko Suwa:
Neural network-based prediction of transmembrane -strand segments in outer membrane proteins.
Journal of Computational Chemistry 25(5): 762-767 (2004) |
10 | | K. Abdulla Bava,
M. Michael Gromiha,
Hatsuho Uedaira,
Koji Kitajima,
Akinori Sarai:
ProTherm, version 4.0: thermodynamic database for proteins and mutants.
Nucleic Acids Research 32(Database-Issue): 120-121 (2004) |
2003 |
9 | | Shandar Ahmad,
M. Michael Gromiha,
Akinori Sarai:
RVP-net: online prediction of real valued accessible surface area of proteins from single sequences.
Bioinformatics 19(14): 1849-1851 (2003) |
8 | EE | M. Michael Gromiha:
Importance of Native-State Topology for Determining the Folding Rate of Two-State Proteins.
Journal of Chemical Information and Computer Sciences 43(5): 1481-1485 (2003) |
7 | EE | Shandar Ahmad,
M. Michael Gromiha:
Design and training of a neural network for predicting the solvent accessibility of proteins.
Journal of Computational Chemistry 24(11): 1313-1320 (2003) |
2002 |
6 | | Shandar Ahmad,
M. Michael Gromiha:
NETASA: neural network based prediction of solvent accessibility.
Bioinformatics 18(6): 819-824 (2002) |
5 | | M. Michael Gromiha,
Hatsuho Uedaira,
Jianghong An,
Samuel Selvaraj,
Ponraj Prabakaran,
Akinori Sarai:
ProTherm, Thermodynamic Database for Proteins and Mutants: developments in version 3.0.
Nucleic Acids Research 30(1): 301-302 (2002) |
2001 |
4 | | Ponraj Prabakaran,
Jianghong An,
M. Michael Gromiha,
Samuel Selvaraj,
Hatsuho Uedaira,
Hidetoshi Kono,
Akinori Sarai:
Thermodynamic database for protein-nucleic acid interactions (ProNIT).
Bioinformatics 17(11): 1027-1034 (2001) |
2000 |
3 | EE | Kenji Sayano,
Hidetoshi Kono,
M. Michael Gromiha,
Akinori Sarai:
Multicanonical Monte Carlo calculation of the free-energy map of the base-amino acid interaction.
Journal of Computational Chemistry 21(11): 954-962 (2000) |
2 | | M. Michael Gromiha,
Jianghong An,
Hidetoshi Kono,
Motohisa Oobatake,
Hatsuho Uedaira,
Ponraj Prabakaran,
Akinori Sarai:
ProTherm, version 2.0: thermodynamic database for proteins and mutants.
Nucleic Acids Research 28(1): 283-285 (2000) |
1999 |
1 | | M. Michael Gromiha,
Jianghong An,
Hidetoshi Kono,
Motohisa Oobatake,
Hatsuho Uedaira,
Akinori Sarai:
ProTherm: Thermodynamic Database for Proteins and Mutants.
Nucleic Acids Research 27(1): 286-288 (1999) |