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978-3-540-33105-6 |
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DE-He213 |
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20220223063223.0 |
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cr nn 008mamaa |
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100301s2006 gw | s |||| 0|eng d |
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|a 9783540331056
|9 978-3-540-33105-6
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|a 10.1007/11691730
|2 doi
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|a Q334-342
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|a Data Mining for Biomedical Applications
|h [electronic resource] :
|b PAKDD 2006 Workshop, BioDM 2006, Singapore, April 9, 2006, Proceedings /
|c edited by Jinyan Li, Qiang Yang, Ah-Hwee Tan.
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| 250 |
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|a 1st ed. 2006.
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| 264 |
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2006.
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| 300 |
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|a VIII, 155 p.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a Lecture Notes in Bioinformatics,
|x 2366-6331 ;
|v 3916
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| 505 |
0 |
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|a Keynote Talk -- Exploiting Indirect Neighbours and Topological Weight to Predict Protein Function from Protein-Protein Interactions -- Database and Search -- A Database Search Algorithm for Identification of Peptides with Multiple Charges Using Tandem Mass Spectrometry -- Filtering Bio-sequence Based on Sequence Descriptor -- Automatic Extraction of Genomic Glossary Triggered by Query -- Frequent Subsequence-Based Protein Localization -- Bio Data Clustering -- gTRICLUSTER: A More General and Effective 3D Clustering Algorithm for Gene-Sample-Time Microarray Data -- Automatic Orthologous-Protein-Clustering from Multiple Complete-Genomes by the Best Reciprocal BLAST Hits -- A Novel Clustering Method for Analysis of Gene Microarray Expression Data -- Heterogeneous Clustering Ensemble Method for Combining Different Cluster Results -- In-silico Diagnosis -- Rule Learning for Disease-Specific Biomarker Discovery from Clinical Proteomic Mass Spectra -- Machine Learning Techniques and Chi-Square Feature Selection for Cancer Classification Using SAGE Gene Expression Profiles -- Generation of Comprehensible Hypotheses from Gene Expression Data -- Classification of Brain Glioma by Using SVMs Bagging with Feature Selection -- Missing Value Imputation Framework for Microarray Significant Gene Selection and Class Prediction -- Informative MicroRNA Expression Patterns for Cancer Classification.
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| 650 |
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|a Artificial intelligence.
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| 650 |
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|a Database management.
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| 650 |
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|a Information storage and retrieval systems.
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| 650 |
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|a Bioinformatics.
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| 650 |
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|a Computer science-Mathematics.
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| 650 |
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|a Mathematical statistics.
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| 650 |
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|a Medical informatics.
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| 650 |
1 |
4 |
|a Artificial Intelligence.
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| 650 |
2 |
4 |
|a Database Management.
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| 650 |
2 |
4 |
|a Information Storage and Retrieval.
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| 650 |
2 |
4 |
|a Bioinformatics.
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| 650 |
2 |
4 |
|a Probability and Statistics in Computer Science.
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| 650 |
2 |
4 |
|a Health Informatics.
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| 700 |
1 |
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|a Li, Jinyan.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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| 700 |
1 |
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|a Yang, Qiang.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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| 700 |
1 |
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|a Tan, Ah-Hwee.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
0 |
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|t Springer Nature eBook
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| 776 |
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8 |
|i Printed edition:
|z 9783540821984
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| 776 |
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8 |
|i Printed edition:
|z 9783540331049
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| 830 |
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|a Lecture Notes in Bioinformatics,
|x 2366-6331 ;
|v 3916
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| 856 |
4 |
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|u https://doi.uam.elogim.com/10.1007/11691730
|z Texto Completo
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| 912 |
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|a ZDB-2-SCS
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| 912 |
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|a ZDB-2-SXCS
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| 912 |
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|a ZDB-2-LNC
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| 950 |
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|a Computer Science (SpringerNature-11645)
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| 950 |
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|a Computer Science (R0) (SpringerNature-43710)
|
