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Articles in Scholarly Journals [Incomplete List]

1. Virus-PLoc: A fusion classifier for predicting the subcellular localization of viral proteins within host and virus-infected cells
   Biopolymers, vol. 85, no. 3, pp. 233–240, 2007
2. Large-scale plant protein subcellular location prediction
   Journal of Cellular Biochemistry, vol. 100, no. 3, pp. 665–678, 2007
3. Peptide reagent design based on physical and chemical properties of amino acid residues
   Journal of Computational Chemistry, vol. 28, no. 12, pp. 2043–2050, 2007
4. Recent progress in protein subcellular location prediction
   Analytical Biochemistry, vol. 370, no. 1, pp. 1–16, 2007
5. PseAAC: A flexible web server for generating various kinds of protein pseudo amino acid composition
   Analytical Biochemistry, 2007
6. MemType-2L: A Web server for predicting membrane proteins and their types by incorporating evolution information through Pse-PSSM
   Biochemical and Biophysical Research Communications, vol. 360, no. 2, pp. 339–345, 2007
7. 3D structure modeling of cytochrome P450 2C19 and its implication for personalized drug design
   Biochemical and Biophysical Research Communications, vol. 355, no. 2, pp. 513–519, 2007
8. Hum-mPLoc: An ensemble classifier for large-scale human protein subcellular location prediction by incorporating samples with multiple sites
   Biochemical and Biophysical Research Communications, vol. 355, no. 4, pp. 1006–1011, 2007
9. Signal-CF: A subsite-coupled and window-fusing approach for predicting signal peptides
   Biochemical and Biophysical Research Communications, vol. 357, no. 3, pp. 633–640, 2007
10. Insights from modeling the 3D structure of NAD(P)H-dependent d-xylose reductase of Pichia stipitis and its binding interactions with NAD and NADP
    Biochemical and Biophysical Research Communications, vol. 359, no. 2, pp. 323–329, 2007
11. EzyPred: A top-down approach for predicting enzyme functional classes and subclasses
    Biochemical and Biophysical Research Communications, vol. 364, no. 1, pp. 53–59, 2007
12. Analogue inhibitors by modifying oseltamivir based on the crystal neuraminidase structure for treating drug-resistant H5N1 virus
    Biochemical and Biophysical Research Communications, vol. 362, no. 2, pp. 525–531, 2007
13. Signal-3L: A 3-layer approach for predicting signal peptides
    Biochemical and Biophysical Research Communications, vol. 363, no. 2, pp. 297–303, 2007
14. Computational studies of the binding mechanism of calmodulin with chrysin
    Biochemical and Biophysical Research Communications, vol. 358, no. 4, pp. 1102–1107, 2007
15. Corrigendum to “3D structure modeling of cytochrome P450 2C19 and its implication for personalized drug design” [Biochem. Biophys. Res. Commun. 355 (2007) 513–519]
    Biochemical and Biophysical Research Communications, vol. 357, no. 1, pp. 330–330, 2007
16. Molecular insights of SAH enzyme catalysis and implication for inhibitor design
    Journal of Theoretical Biology, vol. 244, no. 4, pp. 692–702, 2007
17. Euk-mPLoc: A Fusion Classifier for Large-Scale Eukaryotic Protein Subcellular Location Prediction by Incorporating Multiple Sites
    Journal of Proteome Research, vol. 0, no. 0, pp. 0–0, 2007
18. Using a New Alignment Kernel Function to Identify Secretory Proteins
    Protein and Peptide Letters, vol. 14, no. 2, pp. 203–208, 2007
19. Prediction of Protein Structure Classes with Pseudo Amino Acid Composition and Fuzzy Support Vector Machine Network
    Protein and Peptide Letters, vol. 14, no. 8, pp. 811–815, 2007
20. Predicting the affinity of epitope-peptides with class I MHC molecule HLA-A*0201: an application of amino acid-based peptide prediction
    Protein Engineering Design and Selection, vol. 20, no. 9, pp. 417–423, 2007
21. Digital Coding of Amino Acids Based on Hydrophobic Index
    Protein and Peptide Letters, vol. 14, no. 9, pp. 871–875, 2007
22. Gpos-PLoc: an ensemble classifier for predicting subcellular localization of Gram-positive bacterial proteins
    Protein Engineering Design and Selection, vol. 20, no. 1, pp. 39–46, 2007
23. Nuc-PLoc: a new web-server for predicting protein subnuclear localization by fusing PseAA composition and PsePSSM
    Protein Engineering Design and Selection, vol. 20, no. 11, pp. 561–567, 2007
24. Methodology development for predicting subcellular localization and other attributes of proteins
    Expert Review of Proteomics, vol. 4, no. 4, pp. 453–463, 2007
25. Inhibitor Design for SARS Coronavirus Main Protease Based on “Distorted Key Theory”
    Medicinal Chemistry, vol. 3, no. 1, pp. 1–6, 2007
26. Agaritine and Its Derivatives Are Potential Inhibitors against HIV Proteases
    Medicinal Chemistry, vol. 3, no. 3, pp. 221–226, 2007
27. Screening for New Agonists Against Alzheimer's Disease
    Medicinal Chemistry, vol. 3, no. 5, pp. 488–493, 2007
28. Molecular Modeling Studies of Peptide Drug Candidates against SARS
    Medicinal Chemistry, vol. 2, no. 3, pp. 309–314, 2006
29. Ensemble classifier for protein fold pattern recognition
    Bioinformatics, vol. 22, no. 14, pp. 1717–1722, 2006
30. Journal of Proteome Research, vol. 5, no. 8, pp. 1888–1897, 2006
31. Progress in Computational Approach to Drug Development Against SARS
    Current Medicinal Chemistry, vol. 13, no. 27, pp. 3263–3270, 2006
32. Predicting Protein Structural Class with AdaBoost Learner
    Protein and Peptide Letters, vol. 13, no. 5, pp. 489–492, 2006
33. Journal of Proteome Research, vol. 5, no. 2, pp. 316–322, 2006
34. Journal of Proteome Research, vol. 5, no. 12, pp. 3420–3428, 2006
35. Fuzzy KNN for predicting membrane protein types from pseudo-amino acid composition
    Journal of Theoretical Biology, vol. 240, no. 1, pp. 9–13, 2006
36. Using stacked generalization to predict membrane protein types based on pseudo-amino acid composition
    Journal of Theoretical Biology, vol. 242, no. 4, pp. 941–946, 2006
37. Using LogitBoost classifier to predict protein structural classes
    Journal of Theoretical Biology, vol. 238, no. 1, pp. 172–176, 2006
38. Hum-PLoc: A novel ensemble classifier for predicting human protein subcellular localization
    Biochemical and Biophysical Research Communications, vol. 347, no. 1, pp. 150–157, 2006
39. A novel fingerprint map for detecting SARS-CoV
    Journal of Pharmaceutical and Biomedical Analysis, vol. 41, no. 1, pp. 246–250, 2006
40. A probability cellular automaton model for hepatitis B viral infections
    Biochemical and Biophysical Research Communications, vol. 342, no. 2, pp. 605–610, 2006
41. Insights from modeling the 3D structure of H5N1 influenza virus neuraminidase and its binding interactions with ligands?
    Biochemical and Biophysical Research Communications, vol. 344, no. 3, pp. 1048–1055, 2006
42. Prediction of protease types in a hybridization space
    Biochemical and Biophysical Research Communications, vol. 339, no. 3, pp. 1015–1020, 2006
43. Prediction of protein subcellular location using hydrophobic patterns of amino acid sequence
    Computational Biology and Chemistry, vol. 30, no. 5, pp. 367–371, 2006
44. Heuristic molecular lipophilicity potential (HMLP): Lipophilicity and hydrophilicity of amino acid side chains
    Journal of Computational Chemistry, vol. 27, no. 6, pp. 685–692, 2006
45. Using pseudo amino acid composition to predict protein structural classes: Approached with complexity measure factor
    Journal of Computational Chemistry, vol. 27, no. 4, pp. 478–482, 2006
46. Predicting protein subcellular location by fusing multiple classifiers
    Journal of Cellular Biochemistry, vol. 99, no. 2, pp. 517–527, 2006
47. Heuristic molecular lipophilicity potential (HMLP): A 2D-QSAR study to LADH of molecular family pyrazole and derivatives
    Journal of Computational Chemistry, vol. 26, no. 5, pp. 461–470, 2005
48. Using Fourier Spectrum Analysis and Pseudo Amino Acid Composition for Prediction of Membrane Protein Types
    The Protein Journal, vol. 24, no. 6, pp. 385–389, 2005
49. Boosting classifier for predicting protein domain structural class
    Biochemical and Biophysical Research Communications, vol. 334, no. 1, pp. 213–217, 2005
50. Predicting protein subnuclear location with optimized evidence-theoretic K-nearest classifier and pseudo amino acid composition
    Biochemical and Biophysical Research Communications, 2005
51. Prediction of protein signal sequences and their cleavage sites by statistical rulers
    Biochemical and Biophysical Research Communications, vol. 338, no. 2, pp. 1005–1011, 2005
52. Theoretical studies of Alzheimer’s disease drug candidate 3-[(2,4-dimethoxy)benzylidene]-anabaseine (GTS-21) and its derivatives
    Biochemical and Biophysical Research Communications, vol. 338, no. 2, pp. 1059–1064, 2005
53. Corrigendum to ?Predicting protein structural class by functional domain composition? [Biochem. Biophys. Res. Commun. 321 (2004) 1007?1009]
    Biochemical and Biophysical Research Communications, vol. 329, no. 4, pp. 1362–1362, 2005
54. Low-frequency Fourier spectrum for predicting membrane protein types
    Biochemical and Biophysical Research Communications, vol. 336, no. 3, pp. 737–739, 2005
55. Using GO-PseAA predictor to identify membrane proteins and their types
    Biochemical and Biophysical Research Communications, vol. 327, no. 3, pp. 845–847, 2005
56. Using cellular automata to generate image representation for biological sequences
    Amino Acids, vol. 28, no. 1, pp. 29–35, 2005
57. Modeling the tertiary structure of human cathepsin-E
    Biochemical and Biophysical Research Communications, vol. 331, no. 1, pp. 56–60, 2005
58. SLLE for predicting membrane protein types
    Journal of Theoretical Biology, vol. 232, no. 1, pp. 7–15, 2005
59. Predicting enzyme family classes by hybridizing gene product composition and pseudo-amino acid composition
    Journal of Theoretical Biology, vol. 234, no. 1, pp. 145–149, 2005
60. Using optimized evidence-theoretic K-nearest neighbor classifier and pseudo-amino acid composition to predict membrane protein types
    Biochemical and Biophysical Research Communications, vol. 334, no. 1, pp. 288–292, 2005
61. Assessment of chemical libraries for their druggability
    Computational Biology and Chemistry, vol. 29, no. 1, pp. 55–67, 2005
62. Molecular modeling and chemical modification for finding peptide inhibitor against severe acute respiratory syndrome coronavirus main proteinase
    Analytical Biochemistry, vol. 337, no. 2, pp. 262–270, 2005
63. Using supervised fuzzy clustering to predict protein structural classes
    Biochemical and Biophysical Research Communications, vol. 334, no. 2, pp. 577–581, 2005
64. Predicting membrane protein type by functional domain composition and pseudo-amino acid composition
    Journal of Theoretical Biology, 2005
65. Journal of Proteome Research, vol. 4, no. 3, pp. 967–971, 2005
66. An application of gene comparative image for predicting the effect on replication ratio by HBV virus gene missense mutation
    Journal of Theoretical Biology, vol. 235, no. 4, pp. 555–565, 2005
67. Journal of Chemical Information and Modeling , vol. 45, no. 2, pp. 407–413, 2005
68. Journal of Proteome Research, vol. 4, no. 1, pp. 109–111, 2005
69. Journal of Proteome Research, vol. 4, no. 4, pp. 1413–1418, 2005
70. Journal of Proteome Research, vol. 4, no. 5, pp. 1681–1686, 2005
71. Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes
    Bioinformatics, vol. 21, no. 1, pp. 10–19, 2005
72. A New Nucleotide-composition Based Fingerprint of SARS-CoV with Visualization Analysis
    Medicinal Chemistry, vol. 1, no. 1, pp. 39–47, 2005
73. Application of Bioinformatics in Search for Cleavable Peptides of SARSCoV Mpro and Chemical Modification of Octapeptides
    Medicinal Chemistry, vol. 1, no. 3, pp. 209–213, 2005
74. Editorial [Hot Topic: Biomedicine & Bioinformatics (Guest Editor: Kuo-Chen Chou)]
    Current Protein and Peptide Science, vol. 6, no. 5, pp. 397–398, 2005
75. Computational Methods for Protein-Protein Interaction and their Application
    Current Protein and Peptide Science, vol. 6, no. 5, pp. 443–449, 2005
76. Pattern Recognition Methods for Protein Functional Site Prediction
    Current Protein and Peptide Science, vol. 6, no. 5, pp. 479–491, 2005
77. HIV-1 gp120 V3 Loop for Structure-Based Drug Design
    Current Protein and Peptide Science, vol. 6, no. 5, pp. 413–422, 2005
78. Progress in Protein Structural Class Prediction and its Impact to Bioinformatics and Proteomics
    Current Protein and Peptide Science, vol. 6, no. 5, pp. 423–436, 2005
79. Polyprotein cleavage mechanism of SARS CoV M and chemical modification of the octapeptide
    Peptides, vol. 25, no. 11, pp. 1857–1864, 2004
80. Predicting the linkage sites in glycoproteins using bio-basis function neural network
    Bioinformatics, vol. 20, no. 6, pp. 903–908, 2004
81. Predicting subcellular localization of proteins in a hybridization space
    Bioinformatics, vol. 20, no. 7, pp. 1151–1156, 2004
82. Predicting enzyme family class in a hybridization space
    Protein Science, vol. 13, no. 11, pp. 2857–2863, 2004
83. Bio-support vector machines for computational proteomics
    Bioinformatics, vol. 20, no. 5, pp. 735–741, 2004
84. Journal of Chemical Information and Computer Sciences, vol. 44, no. 3, pp. 1111–1122, 2004
85. Journal of Proteome Research, vol. 3, no. 6, pp. 1284–1288, 2004
86. Journal of Proteome Research, vol. 3, no. 5, pp. 1069–1072, 2004
87. Weighted-support vector machines for predicting membrane protein types based on pseudo-amino acid composition
    Protein Engineering Design and Selection, vol. 17, no. 6, pp. 509–516, 2004
88. Journal of Proteome Research, vol. 3, no. 4, pp. 856–861, 2004
89. Predicting protein localization in budding Yeast
    Bioinformatics, vol. 21, no. 7, pp. 944–950, 2004
90. Identify catalytic triads of serine hydrolases by support vector machines
    Journal of Theoretical Biology, vol. 228, no. 4, pp. 551–557, 2004
91. Insights from modelling the 3D structure of the extracellular domain of $alpha;7 nicotinic acetylcholine receptor*1
    Biochemical and Biophysical Research Communications, vol. 319, no. 2, pp. 433–438, 2004
92. Application of SVM to predict membrane protein types
    Journal of Theoretical Biology, vol. 226, no. 4, pp. 373–376, 2004
93. Using complexity measure factor to predict protein subcellular location
    Amino Acids, vol. 28, no. 1, pp. 57–61, 2004
94. Modelling extracellular domains of GABA-A receptors: subtypes 1, 2, 3, and 5
    Biochemical and Biophysical Research Communications, vol. 316, no. 3, pp. 636–642, 2004
95. Predicting 22 protein localizations in budding yeast
    Biochemical and Biophysical Research Communications, vol. 323, no. 2, pp. 425–428, 2004
96. Using GO-PseAA predictor to predict enzyme sub-class
    Biochemical and Biophysical Research Communications, vol. 325, no. 2, pp. 506–509, 2004
97. Prediction of protein subcellular locations by GO?FunD?PseAA predictor
    Biochemical and Biophysical Research Communications, vol. 320, no. 4, pp. 1236–1239, 2004
98. Predicting protein structural class by functional domain composition
    Biochemical and Biophysical Research Communications, vol. 321, no. 4, pp. 1007–1009, 2004
99. Predicting subcellular localization of proteins by hybridizing functional domain composition and pseudo-amino acid composition
    Journal of Cellular Biochemistry, vol. 91, no. 6, pp. 1197–1203, 2004
100. A novel approach to predict active sites of enzyme molecules
     Proteins: Structure, Function, and Bioinformatics, vol. 55, no. 1, pp. 77–82, 2004
101. Prediction of protein secondary structure content by artificial neural network
     Journal of Computational Chemistry, vol. 24, no. 6, pp. 727–731, 2003
102. Predicting protein quaternary structure by pseudo amino acid composition
     Proteins: Structure, Function, and Genetics, vol. 53, no. 2, pp. 282–289, 2003
103. Prediction and classification of protein subcellular location?sequence-order effect and pseudo amino acid composition
     Journal of Cellular Biochemistry, vol. 90, no. 6, pp. 1250–1260, 2003
104. Erratum to “Binding mechanism of coronavirus main proteinase with ligands and its implication to drug design against SARS” [Biochem. Biophys. Res. Commun. 308 (2003) 148–151]
     Biochemical and Biophysical Research Communications, vol. 310, no. 2, p. 675, 2003
105. Support Vector Machines for Prediction of Protein Domain Structural Class
     Journal of Theoretical Biology, vol. 221, no. 1, pp. 115–120, 2003
106. A new hybrid approach to predict subcellular localization of proteins by incorporating gene ontology
     Biochemical and Biophysical Research Communications, vol. 311, no. 3, pp. 743–747, 2003
107. Nearest neighbour algorithm for predicting protein subcellular location by combining functional domain composition and pseudo-amino acid composition
     Biochemical and Biophysical Research Communications, vol. 305, no. 2, pp. 407–411, 2003
108. Correlations of amino acids in proteins
     Peptides, vol. 24, no. 12, pp. 1863–1869, 2003
109. Journal of Proteome Research, vol. 2, no. 3, pp. 331–331, 2003
110. Support Vector Machine for predicting a-turn types
     Peptides, vol. 24, no. 4, pp. 629–630, 2003
111. Support vector machines for prediction of protein signal sequences and their cleavage sites
     Peptides, vol. 24, no. 1, pp. 159–161, 2003
112. Binding mechanism of coronavirus main proteinase with ligands and its implication to drug design against SARS
     Biochemical and Biophysical Research Communications, vol. 308, no. 1, pp. 148–151, 2003
113. Journal of Chemical Information and Computer Sciences, vol. 43, no. 6, pp. 1748–1753, 2003
114. Prediction of ß-turns with learning machines
     Peptides, vol. 24, no. 5, pp. 665–669, 2003
115. Journal of Proteome Research, vol. 2, no. 2, pp. 183–190, 2003
116. Prediction of Protein Signal Sequences
     Current Protein & Peptide Science, vol. 3, no. 6, pp. 615–622, 2002
117. Journal of Proteome Research, vol. 1, no. 5, pp. 429–433, 2002
118. Using Functional Domain Composition and Support Vector Machines for Prediction of Protein Subcellular Location
     Journal of Biological Chemistry, vol. 277, no. 48, pp. 45765–45769, 2002
119. Artificial neural network model for predicting protein subcellular location
     Computers & Chemistry, vol. 26, no. 2, pp. 179–182, 2002
120. Prediction of protein structural classes by support vector machines
     Computers & Chemistry, vol. 26, no. 3, pp. 293–296, 2002
121. Support vector machines for predicting the specificity of GalNAc-transferase
     Peptides, vol. 23, no. 1, pp. 205–208, 2002
122. Artificial neural network method for predicting protein secondary structure content
     Computers & Chemistry, vol. 26, no. 4, pp. 347–350, 2002
123. Prediction of the Tertiary Structure of the ß-Secretase Zymogen
     Biochemical and Biophysical Research Communications, vol. 292, no. 3, pp. 702–708, 2002
124. Support vector machines for prediction of protein subcellular location by incorporating quasi-sequence-order effect
     Journal of Cellular Biochemistry, vol. 84, no. 2, pp. 343–348, 2002
125. Identification of the N-terminal functional domains of Cdk5 by molecular truncation and computer modeling
     Proteins: Structure, Function, and Genetics, vol. 48, no. 3, pp. 447–453, 2002
126. Support vector machines for the classification and prediction of ?-turn types
     Journal of Peptide Science, vol. 8, no. 7, pp. 297–301, 2002
127. Prediction of protein cellular attributes using pseudo-amino acid composition
     Proteins: Structure, Function, and Genetics, vol. 44, no. 1, pp. 60–60, 2001
128. Support vector machines for predicting HIV protease cleavage sites in protein
     Journal of Computational Chemistry, vol. 23, no. 2, pp. 267–274, 2001
129. Prediction of protein cellular attributes using pseudo-amino acid composition
     Proteins: Structure, Function, and Genetics, vol. 43, no. 3, pp. 246–255, 2001
130. Prediction of signal peptides using scaled window
     Peptides, vol. 22, no. 12, pp. 1973–1979, 2001
131. Using neural networks for prediction of domain structural classes
     Biochimica et Biophysica Acta (BBA) - Protein Structure and Molecular Enzymology, vol. 1476, no. 1, pp. 1–2, 2000
132. Prediction of the tertiary structure of a caspase-9/inhibitor complex
     FEBS Letters, vol. 470, no. 3, pp. 249–256, 2000
133. Prediction of protein signal sequences and their cleavage sites
     Proteins: Structure, Function, and Genetics, vol. 42, no. 1, pp. 136–139, 2000
134. Prediction of Tight Turns and Their Types in Proteins
     Analytical Biochemistry, vol. 286, no. 1, pp. 1–16, 2000
135. Prediction of Protein Subcellular Locations by Incorporating Quasi-Sequence-Order Effect
     Biochemical and Biophysical Research Communications, vol. 278, no. 2, pp. 477–483, 2000
136. Using Neural Networks for Prediction of Subcellular Location of Prokaryotic and Eukaryotic Proteins
     Molecular Cell Biology Research Communications, vol. 4, no. 3, pp. 172–173, 2000
137. Support Vector Machines for Prediction of Protein Subcellular Location
     Molecular Cell Biology Research Communications, vol. 4, no. 4, pp. 230–233, 2000
138. Prediction of Protein Structural Classes and Subcellular Locations
     Current Protein and Peptide Science, vol. 1, no. 2, pp. 171–208, 2000
139. A Model of the Complex between Cyclin-Dependent Kinase 5 and the Activation Domain of Neuronal Cdk5 Activator
     Biochemical and Biophysical Research Communications, vol. 259, no. 2, pp. 420–428, 1999
140. Prediction of membrane protein types and subcellular locations
     Proteins: Structure, Function, and Genetics, vol. 34, no. 1, pp. 137–153, 1999
141. Artificial Neural Network Model for Predicting a-Turn Types
     Analytical Biochemistry, vol. 268, no. 2, pp. 407–409, 1999
142. A Key Driving Force in Determination of Protein Structural Classes
     Biochemical and Biophysical Research Communications, vol. 264, no. 1, pp. 216–224, 1999
143. Classification and prediction of ß–turn types by neural network
     Advances in Engineering Software, vol. 30, no. 5, pp. 347–352, 1999
144. Journal of Protein Chemistry, vol. 18, no. 4, pp. 473–480, 1999
145. Artificial neural network model for predicting HIV protease cleavage sites in protein
     Advances in Engineering Software, vol. 29, no. 2, pp. 119–128, 1998
146. Journal of Protein Chemistry, vol. 17, no. 3, pp. 209–217, 1998
147. Using Discriminant Function for Prediction of Subcellular Location of Prokaryotic Proteins
     Biochemical and Biophysical Research Communications, vol. 252, no. 1, pp. 63–68, 1998
148. Artificial neural network method for predicting HIV protease cleavage sites in protein
     Journal of Protein Chemistry, vol. 17, no. 7, pp. 607–615, 1998
149. Journal of Protein Chemistry, vol. 17, no. 4, pp. 363–376, 1998
150. Prediction of the tertiary structure and substrate binding site of caspase-8
     FEBS Letters, vol. 419, no. 1, pp. 49–54, 1997
151. Journal of Protein Chemistry, vol. 16, no. 7, pp. 689–700, 1997
152. Journal of Protein Chemistry, vol. 16, no. 8, pp. 765–773, 1997
153. Journal of Protein Chemistry, vol. 16, no. 6, pp. 575–595, 1997
154. The benzylthio-pyrimidine U-31,355, a potent inhibitor of HIV-1 reverse transcriptase
     Biochemical Pharmacology, vol. 51, no. 6, pp. 743–750, 1996
155. Beat motion in DNA double helix and a mechanism of energy exchange between its two strands with microwave frequency
     Chemical Physics, vol. 206, no. 3, pp. 271–277, 1996
156. Artificial Neural Network Model for Predicting the Specificity of GalNAc-transferase
     Analytical Biochemistry, vol. 243, no. 2, pp. 284–285, 1996
157. Prediction of Human Immunodeficiency Virus Protease Cleavage Sites in Proteins
     Analytical Biochemistry, vol. 233, no. 1, pp. 1–14, 1996
158. Predicting human immunodeficiency virus protease cleavage sites in proteins by a discriminant function method
     Proteins: Structure, Function, and Genetics, vol. 24, no. 1, pp. 51–72, 1996
159. Neural Network Prediction of the HIV-1 Protease Cleavage Sites
     Journal of Theoretical Biology, vol. 177, no. 4, pp. 369–379, 1995
160. The convergence-divergence duality in lectin domains of selectin family and its implications
     FEBS Letters, vol. 363, no. 1-2, pp. 123–126, 1995
161. Does the folding type of a protein depend on its amino acid composition?
     FEBS Letters, vol. 363, no. 1-2, pp. 127–131, 1995