Table of Contents

• Preface to the proceedingsDavid B. Fogel. [doi]
• Cluster analysis of the p53 genetic regulatory network: topology and biologyJennifer Hallinan. 1-8 [doi]
• Analyzing gene expression data for childhood medulloblastoma survival with artificial neural networksAjit Narayanan, Evangelia Nana, Ed Keedwell. 9-16 [doi]
• An efficient method for fuzzy identification of regulatory events in gene expression time series dataL. Gwenn Volkert, Nawar Malhis. 17-24 [doi]
• Gene expression correlation and gene ontology-based similarity: an assessment of quantitative relationshipsHaiying Wang, Francisco Azuaje, Olivier Bodenreider, Joaquín Dopazo. 25-31 [doi]
• Genetic network reverse-engineering and network size; can we identify large GRNs?Carey Pridgeon, David Corne. 32-36 [doi]
• A multifuzzy filtering approach to reliable gene expression profile analysisHuseyin Seker. 37-40 [doi]
• Feature selection in proteomic pattern data with support vector machinesKees Jong, Elena Marchiori, Michèle Sebag, Aad van der Vaart. 41-48 [doi]
• A variant of SVM-RFE for gene selection in cancer classification with expression dataKaibo Duan, Jagath C. Rajapakse. 49-55 [doi]
• Model and feature selection in microarray classificationDavid A. Peterson, Michael H. Thaut. 56-60 [doi]
• Multiclass protein fold recognition using multiobjective evolutionary algorithmsStanley Y. M. Shi, Ponnuthurai N. Suganthan, Kalyanmoy Deb. 61-66 [doi]
• Two-stage support vector machines to protein relative solvent accessibility predictionMinh Ngoc Nguyen 0002, Jagath C. Rajapakse. 67-72 [doi]
• Granular support vector machines for medical binary classification problemsYuchun Tang, Bo Jin, Yi Sun, Yan-Qing Zhang. 73-78 [doi]
• Multiple DNA sequence approximate matchingKathleen M. Kaplan, John J. Kaplan. 79-86 [doi]
• Identification of botanical specimens using artificial neural networksJonathan Y. Clark. 87-94 [doi]
• Grouping and visualizing human endogenous retroviruses by bootstrapping median self-organizing mapsMerja Oja, Göran O. Sperber, Jonas Blomberg, Samuel Kaski. 95-101 [doi]
• Inferring neutral evolution from Parkinson's disease genesGavyn Pang, Jagath C. Rajapakse. 102-107 [doi]
• A new distance metric and its application in phylogenetic tree constructionWang Long-Hui, Liu Juan, Zhou Huai-Bei, Shi Feng. 108-115 [doi]
• Analyzing fuzzy partitions of Saccharomyces cerevisiae cell-cycle gene expression data by Bayesian validation methodSi-Ho Yoo, Chanho Park, Sung-Bae Cho. 116-122 [doi]
• Classification of event-related potentials in individuals at risk for alcoholism using wavelet transform and artificial neural networkCarla D. Lopes, Josias O. Mainardi, Milton A. Zaro, Altamiro Amadeu Susin. 123-128 [doi]
• Electronic nose inhibition in a spiking neural network for noise cancellationJacob N. Allen, Hoda S. Abdel-Aty-Zohdy, Robert L. Ewing. 129-133 [doi]
• Transmembrane segments prediction with support vector machine based on high performance encoding schemesHae-Jin Hu, Robert W. Harrison, Phang C. Tai, Yi Pan. 134-139 [doi]
• Statistical neural networks and support vector machine for the classification of genetic mutations in ovarian cancerMuhammad Shoaib B. Sehgal, Iqbal Gondal, Laurence Dooley. 140-146 [doi]
• Graphical approach for motif recognition in DNA sequencesXiao Yang, Jagath C. Rajapakse. 147-152 [doi]
• High sensitivity technique for translation initiation site detectionLoi Sy Ho, Jagath C. Rajapakse. 153-159 [doi]
• Comparison of discrimination methods for peptide classification in tandem mass spectrometryAnthony J. Bonner, Han Liu. 160-167 [doi]
• Protein family classification using structural and sequence informationScott F. Smith. 168-174 [doi]
• Factoring tertiary classification into binary classification improves neural network for protein secondary structure predictionWei Zhong, Gulsah Altun, Hae-Jin Hu, Robert W. Harrison, Phang C. Tai, Yi Pan. 175-181 [doi]
• A comparison of sequence alignment algorithms for measuring secondary structure similarityL. Gwenn Volkert, Deborah Stoffer. 182-189 [doi]
• A comparison of evolved finite state classifiers and interpolated Markov models for improving PCR primer designDaniel A. Ashlock, Scott J. Emrich, Kenneth Mark Bryden, Steven M. Corns, Tsui-Jung Wen, Patrick S. Schnable. 190-197 [doi]
• Secret sequence comparison in distributed computing environments by interval samplingKen-ichi Kurata, Vincent Breton, Hiroshi Nakamura. 198-205 [doi]
• Evolutionary approach to NOE paths assignment in RNA structure elucidationJacek Blazewicz, Marta Szachniuk, Adam Wojtowicz. 206-213 [doi]
• Comparison of dynamic programming and evolutionary algorithms for RNA secondary structure predictionAlain Deschênes, Kay C. Wiese, Jagdeep Poonian. 214-222 [doi]
• A parallel evolutionary algorithm for RNA secondary structure prediction using stacking-energies (INN and INN-HB)Andrew Hendriks, Alain Deschênes, Kay C. Wiese. 223-230 [doi]
• Locally sensitive backtranslation based on multiple sequence alignmentRosalba Giugno, Alfredo Pulvirenti, Marco Ragusa, Loredana Facciola, Laura Patelmo, Valentina Di Pietro, Cinzia Di Pietro, Michele Purrello, Alfredo Ferro. 231-237 [doi]
• Evolutionary optimization of interval rules for drug designJ. Paetz. 238-243 [doi]
• Extracting and mining protein-protein interaction network from biomedical literatureXiaohua Hu, Illhoi Yoo, Il-Yeol Song, Min Song, Jianchao Han, Mark Lechner. 244-251 [doi]
• A memetic clustering algorithm for the functional partition of genes based on the gene ontologyNora Speer, Christian Spieth, Andreas Zell. 252-259 [doi]
• Self-adaptive evolutionary algorithm based methods for quantification in metabolic systemsJing Yang 0006, Sarawan Wongsa, Visakan Kadirkamanathan, Stephen A. Billings, Phillip C. Wright. 260-267 [doi]
• 4C: an adaptive artificial ants clustering algorithmXiao-hua Xu, Ling Chen, Yixin Chen. 268-275 [doi]