| JOURNAL CLUB |
| journal clubÀº ¸ÅÁÖ Åä¿äÀÏ 9½Ã¿¡ ÀÖ½À´Ï´Ù |
| 2006 | 2005 | 2004 | 2003 | 2002 |
| 2006 | May(05) | |||
| 6 | ¿ÂÁ¤Çå | |||
| 6 | ¿ìÁ¤ÈÆ | |||
| 13 | ³ª¿µÁö | |||
| 13 | Á¤¿ë | |||
| 20 | Á¤Å¼ö | |||
| 20 | ±èÁöÈÆ | |||
| 27 | Á¶¼º¹ü | |||
| 27 | Á¤ÈñÁØ | |||
| 2006 | April(04) | |||
| 1 | ¿ìÁ¤ÈÆ | |||
| 1 | ¹ÚÀ¯¶û | |||
| 8 | Á¤¿ë | |||
| 8 | ±èÁöÈÆ | |||
| 15 | Á¶¼º¹ü | |||
| 15 | Á¤ÈñÁØ | |||
| 22 | ¹ÚÂùÈñ | |||
| 22 | ¿ÂÁ¤Çå | |||
| 29 | ±è¹Î±¸ | |||
| 29 | ¹ÚÀ¯¶û | |||
| 2006 | March(03) | |||
| 4 | ±èÁöÈÆ | |||
| 4 | Á¶¼º¹ü | |||
| 11 | ¼ºÁ¤È¯ | |||
| 11 | ±è¹Î±¸ | |||
| 18 | Á¤Å¼ö | |||
| 18 | ¿ÂÁ¤Çå | |||
| 25 | Á¤ÈñÁØ | |||
| 25 | ³ª¿µÁö | |||
| 2006 | February(02) | |||
| 4 | ³ª¿µÁö | |||
| 4 | ±è¹Î±¸ | |||
| 11 | ÀÌÇý¿ø | |||
| 11 | ¹ÚÀ¯¶û | |||
| 18 | Á¤ÈñÁØ | miRBase: microRNA sequences, targets and gene nomenclature |
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| 18 | ¿ìÁ¤ÈÆ | |||
| 25 | Á¤¿ë | |||
| 25 | Á¤Å¼ö | |||
| 2006 | January(01) | |||
| 07 | ³ª¿µÁö | |||
| 07 | À±Çý¼º | |||
| 14 | ¿ÂÁ¤Çå | |||
| 14 | Á¤Å¼ö | |||
| 21 | ±èÁöÈÆ | |||
| 21 | Á¶¼º¹ü | Signal transduction profiling of individual tumor samples |
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| 2005 | December(12) | |||
| 3 | ¹ÚÀ¯¶û | ONTOFUSION: Ontology-based integration of genomic and clinical databases |
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| 3 | Á¤Å¼ö | PLAID MODELS FOR GENE EXPRESSION DATA |
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| 10 | ±èÁöÈÆ | L2L: a simple tool for discovering the hidden significance in microarray expression data |
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| 17 | Á¤ÈñÁØ | Linking pathway gene expressions to the growth inhibition response from the National Cancer Institute's anticancer screen and drug mechanism of action |
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| 17 | Á¶¼º¹ü | |||
| 24 | ¿ìÁ¤ÈÆ | Dual activation of pathways regulated by steroid receptors and peptide growth factors in primary prostate cancer revealed by Factor Analysis of microarray data |
||
| 24 | ±è¹Î±¸ | |||
| 31 | ÀÌÇý¿ø | |||
| 31 | ¹ÚÀ¯¶û | |||
| 2005 | November(11) | |||
| 5 | ¿ìÁ¤ÈÆ | |||
| 5 | ¿ÂÁ¤Çå | |||
| 12 | ±è¹Î±¸ | |||
| 12 | ±è¹ÌÇö | |||
| 26 | ³ª¿µÁö | |||
| 26 | ÀÌÇý¿ø | |||
|   | ECCB2005 Review | |||
| 10.31 | ¿ìÁ¤ÈÆ | |||
| 10.31 | ÀÌÇý¿ø | |||
| 10.31 | Á¤ÈñÁØ | |||
| 10.31 | ±è¹Î±¸ | Analyzing microarray data using quantitative association rules |
||
| 10.31 | Á¶¼º¹ü | |||
| 2005 | October(10) | |||
| 1 | ±è¹ÌÇö | |||
| 1 | ³ª¿µÁö | |||
| 8 | ¿ìÁ¤ÈÆ | |||
| 8 | ¿ÂÁ¤Çå | |||
| 15 | ÀÌÇý¿ø | |||
| 15 | ±èÁöÈÆ | |||
| 22 | ¹ÚÂùÈñ | |||
| 22 | À±Çý¼º | |||
| 29 | Á¶¼º¹ü | |||
| 29 | Á¤ÈñÁØ | |||
| 2005 | September(9) | |||
| 3 | ¹ÚÀ¯¶û | |||
| 3 | Á¤ÈñÁØ | |||
| 10 | Á¶¼º¹ü | |||
| 10 | ±è¹Î±¸ | |||
| 24 | Á¤Å¼ö | |||
| 24 | À±Çý¼º | |||
| 24 | ¼ºÁ¤È¯ | Computational biology & microarrays on microRNA research |
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| 2005 | August(8) | |||
| 6 | ¹ÚÀ¯¶û | |||
| 6 | ÀÌÇý¿ø | |||
| 13 | ³ª¿µÁö | |||
| 13 | ¿ìÁ¤ÈÆ | |||
| 20 | ±è¹ÌÇö | |||
| 20 | Á¤Å¼ö | |||
| 27 | ±èÁöÈÆ | |||
| 27 | ¹ÚÂùÈñ | |||
| 2005 | July(7) | |||
| 2 | Á¤Å¼ö | |||
| 2 | ±è¹Î±¸ | |||
| 9 | ¹ÚÂùÈñ | |||
| 9 | ÇÑ¹Ì·É | |||
| 16 | Á¤ÈñÁØ | |||
| 16 | Á¶¼º¹ü | |||
| 23 | ±èÁöÈÆ | |||
| 23 | ¿ÂÁ¤Çå | |||
| 30 | ÇÑ¹Ì·É | |||
| 30 | ±è¿Á±¸ | |||
| 2005 | June(6) | |||
| 4 | Á¶¼º¹ü | |||
| 4 | ±è¹Î±¸ | |||
| 11 | ¹ÚÀ¯¶û | |||
| 11 | ±è¿Á±¸ | |||
| 18 | À±Çý¼º | |||
| 18 | ±è¹ÌÇö | |||
| 25 | ÀÌÇý¿ø | |||
| 25 | ³ª¿µÁö | |||
| 2005 | May(5) | |||
| 7 | ±è¹ÌÇö | |||
| 7 | ³ª¿µÁö | |||
| 14 | Á¤Å¼ö | |||
| 14 | ±èÁöÈÆ | |||
| 21 | ¹ÚÂùÈñ | |||
| 21 | À±Çý¼º | |||
| 28 | Á¤ÈñÁØ | |||
| 28 | À̼ö¿¬ | |||
| 2005 | April(4) | |||
| 2 | ¹ÚÂùÈñ | |||
| 2 | À±Çý¼º | |||
| 9 | Á¤ÈñÁØ | |||
| 9 | À̼ö¿¬ | |||
| 16 | Á¶¼º¹ü | |||
| 16 | ±è¹Î±¸ | |||
| 23 | ÀÌÇý¿ø | |||
| 23 | ±è¿Á±¸ | |||
| 30 | ÇÑ¹Ì·É | |||
| 30 | ¹ÚÀ¯¶û | |||
| 2005 | March(3) | |||
| 7 | ¹ÚÀ¯¶û | |||
| 7 | ±è¹ÌÇö | |||
| 14 | ³ª¿µÁö | |||
| 14 | Á¤Å¼ö | |||
| 26 | Á¤Å¼ö | |||
| 26 | ±èÁöÈÆ | |||
| 2005 | February(2) | |||
| 14 | À̼ö¿¬ | |||
| 14 | ÀÌÇý¿ø | |||
| 21 | ±è¹Î±¸ | |||
| 21 | Á¶¼º¹ü | |||
| 28 | ÇÑ¹Ì·É | |||
| 28 | ±è¿Á±¸ | |||
| 2005 | January(1) | |||
| 03 | ¹ÚÀ¯¶û | |||
| 03 | ±è¹ÌÇö | |||
| 10 | ±èÁöÈÆ | |||
| 10 | ¼ÈÁ¤ | |||
| 24 | Á¤Å¼ö |
Hidden Markov Models Approach to the Analysis of Array CGH Data |
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| 24 | ¹ÚÂùÈñ | |||
| 31 | À±Çý¼º | A graph-theoretic approach to test disparate datatypes |
||
| 31 | Á¤ÈñÁØ | Structuration of Phenotypes / Genotypes through Galois Lattices and Implications | ||
|   | PSB2005 Review | |||
| 17 | Á¤Å¼ö |
GenRate: A Generative Model That Finds and Scores New Genes and Exons in Genomic Microarray Data |
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| 17 | Á¤Å¼ö |
Sparse Factorizations of Gene Expression Guided by Binding Data |
||
| 17 | Á¤ÈñÁØ | Ontology Driven Dynamic Linking of Biology Resources |
||
| 17 | Á¤ÈñÁØ | Parameterization of A Nonlinear Genotype to Phenotype Map Using Molecular networks |
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| 17 | ÇÑ¹Ì·É | GOTREES: Predicting GO associations from protein domain composition using decision trees |
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| 17 | ÇÑ¹Ì·É | Multi-Aspect gene relation analysis |
||
| 17 | ³ª¿µÁö | Explatory Visual Analysis Of Pharmacogenomic Results |
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| 2004 | December(12) | |||
| 4 | ¹ÚÂùÈñ |
|
|
|
| 4 | ¼ÈÁ¤ |
|
|
|
| 11 | À±Çý¼º | Protecting DNA Sequence Anonymity with Generalization Lattices |
||
| 11 | Á¤Å¼ö |
|
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| 18 | Á¤ÈñÁØ | |||
| 18 | ±è¹Î±¸ | |||
| 27 | ÀÌÇý¿ø | |||
| 27 | ÇÑ¹Ì·É | |||
| 2004 | November(11) | |||
| 6 | Á¤Å¼ö | |||
| 6 | ¹ÚÀ¯¶û | |||
| 13 | Á¤ÈñÁØ | |||
| 13 | ÀÌÇý¿ø | |||
| 13 | ÇÑ¹Ì·É | |||
| 20 | ±èÁöÈÆ | |||
| 20 | ±è¹ÌÇö | |||
| 27 | À̼®È£ | |||
| 27 | ¹ÚÀ¯¶û | |||
| 2004 | October(10) | |||
| 02 | À±Çý¼º | Mining Scale-free Networks using Geodesic Clustering |
||
| 02 | ±è¹ÌÇö | |||
| 09 | À̼®È£ | |||
| 09 | ÇÑ¹Ì·É | |||
| 16 | ±è¹Î±¸ | |||
| 16 | ±èÁöÈÆ | |||
| 23 | ¼ÈÁ¤ |
|
|
|
| 25 | ¹ÚÂùÈñ | |||
| 30 | ÀÌÇý¿ø | |||
| 2004 | September(9) | |||
| 4 | Á¤ÈñÁØ | |||
| 4 | ÀÌÇý¿ø | |||
| 11 | ±è¹Î±¸ | Biclustering Algorithms for Biological Data Analysis: A Survey |
||
| 11 | Á¤Å¼ö | |||
| 18 | Á¤ÈñÁØ | Biological data and conceptual modelling methods |
||
| 2004 | August(8) | |||
| 7 | ±èÁöÈÆ | |||
| 7 | À̼®È£ | |||
| 14 | ±è¹ÌÇö | |||
| 14 | ¼ÈÁ¤ | |||
| 21 | ±è¹Î±¸ | |||
| 21 | ±è±â¿ø | |||
| 28 | ¹ÚÀ¯¶û | |||
| 28 | ÇÑ¹Ì·É | |||
|   | ISMB2004 Review | |||
| 31 | Á¤Å¼ö | Inferring quantitative models of regulatory networks from expression data |
||
| 31 | ±è¹Î±¸ | |||
| 31 | ¹ÚÀ¯¶û | Mining MEDLINE for implicit links between dietary substances and diseases |
||
| 31 | ±è±â¿ø | |||
| 31 | ¹ÚÂùÈñ | Into the heart of darkness: large scale clustering of human non-coding DNA |
||
| 31 | ±è¹ÌÇö | |||
| 31 | ÇÑ¹Ì·É | Partial cox regression analysis for high-dimensional microarray gene expression data |
||
| 31 | Á¤ÈñÁØ | |||
| 31 | ÀÌÇý¿ø | |||
| 2004 | July(7) | |||
| 3 | ±èÁöÈÆ(Áë) | |||
| 10 | ¹ÚÂùÈñ | |||
| 10 | À±Çý¼º | |||
| 24 | Á¤Å¼ö | |||
| 24 | ¹ÚÂùÈñ | |||
| 2004 | June(6) | |||
|
5 |
±èÁöÈÆ(H) | |||
| 5 | ¹ÚÀ¯¶û | |||
| 12 | ¼ÈÁ¤ | XML as standard for communicating in a document-based electronic patient record: a 3 years experiment. | ||
| 12 | ±è¹Î±¸ | |||
| 19 | ÇÑ¹Ì·É | |||
| 19 | ±è±â¿ø | |||
| 26 | ÀÌÇý¿ø | |||
| 26 | Á¤ÈñÁØ | |||
| 2004. | May (5) | |||
| 1 | ÇÑ¹Ì·É | Expression profiling to predict postoperative prognosis for estrogen receptor-negative breast cancers by analysis of 25,344 genes on a cDNA microarray | ||
| 1 | ¹ÚÀ¯¶û | Development of common data elements: the experience of and recommendations from the early detection research network | ||
| 8 | ±è±â¿ø | Discovering modes of action for therapeutic compounds using a genome-wide screen of yeast heterozygotes | ||
| 8 | ±èÁöÈÆ(H) | Gene
selection and clustering for time-course and dose-response microarray
experiments using order-restricted inference. |
||
| 15 | ±èÁöÈÆ(Áë) | Quantifying the relationship between co-expression, co-regulation and gene function | ||
| 15 | ¹ÚÂùÈñ | GoMiner: a resource for biological interpretation of genomic and proteomic data | ||
| 22 | Á¤Å¼ö | Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data | ||
| 22 | À±Çý¼º | An Architecture for Biological Information Extraction and Representation | ||
| 29 | ÀÌÁ¤¾Ö | PubMatrix: a tool for multiplex literature mining. | ||
| 2004. | April (4) | |||
| 3 | ¹ÚÁö¿¬ | Biological detection of low radiation doses by combining results of two microarray analysis methods | ||
| 3 | ±èÁöÈÆ(Áë) | Inferring transcriptional regulation relationship from microarray time series data | ||
| 10 | ¼ÈÁ¤ | UML-XML-RDB Model Mapping Solution for Facilitating Information Standardization and Sharing in Construction Industry | ||
| 10 | ÀÌÁ¤¾Ö | Selective automated indexing of findings and diagnoses in radiology reports | ||
| 17 | Á¤Å¼ö | Discovering molecular pathways from protein interaction and gene expression data | ||
| 17 | ±èÁöÈÆ(H) | Differential amplification of gene expression in lens cell lines conditioned to survive peroxide stress | ||
| 24 | ÀÌÇý¿ø | Common structural patterns in human genes. | ||
| 24 | ±è¹Î±¸ | Network-based approach for the comprehensive mapping between biological identifiers | ||
| 2004. | March (3) | |||
| 6 | ÀÌÇý¿ø | Molecular profiling of mouse lung tumors: association with tumor progression, lung development, and human lung adenocarcinomas | ||
| 6 | ±è¹Î±¸ | Meta-databases providing collection of hyperlinks | ||
| 13 | ÇÑ¹Ì·É | Gene expression predictors of breast cancer outcomes | ||
| 13 | ¹ÚÀ¯¶û | Ontology Versioning as an Element of an Ontology-Management Framework | ||
| 20 | ±è±â¿ø | Chipping away at the chip bias: RNA degradation in microarray analysis | ||
| 20 | Á¤ÈñÁØ | The PEPR GeneChip data warehouse, and implementation of a dynamic time series query tool (SGQT) with graphical interface | ||
| 27 | À±Çý¼º | A new distributed data mining model based on similarity | ||
| 27 | ¹ÚÂùÈñ | Pharmacogenetics: potential for individualized drug therapy through genetics | ||
| 2004. | February (2) | |||
| 7 | ±èÁöÈÆ(Áë) | Statistical resynchronization and Bayesian detection of periodically expressed genes | ||
| 7 | ¹ÚÂùÈñ | Automatic extraction of mutations from Medline and cross-validation with OMIM | ||
| 14 | ¹ÚÁö¿¬ | A Mapping Schema and Interface for XML Stores | ||
| 14 | ¼ÈÁ¤ | Presenting XML-based medical discharge letters according to CDA | ||
| 21 | À±Çý¼º | CloseGraph: Mining Closed Frequent Graph Patterns | ||
| 21 | ÀÌÁ¤¾Ö | Towards linking patients and clinical information: detecting UMLS concepts in e-mail | ||
| 28 | Á¤Å¼ö | ESPD: a pattern detection model underlying gene expression profiles | ||
| 28 | Á¤ÈñÁØ | Computational knowledge integration in biopharmaceutical research | ||
| 2004. | January (1) | |||
| 3 | ¼ÈÁ¤ | XPERANTO:
Publishing Object-Relational Data as XML [Reference] Querying XML Views of Relational Data |
||
| 3 | Á¤ÈñÁØ | GenePublisher: Automated analysis of DNA microarray data | ||
| 10 | ÀÌÇý¿ø | Gene expression profile of normal lungs predicts genetic predisposition to lung cancer in mice | ||
| 10 | ±è¹Î±¸ | A protein interaction map of Drosophila melanogaster | ||
| 17 | ÇÑ¹Ì·É | Differentiation of lobular versus ductal breast carcinomas by expression microarray analysis | ||
| 17 | ¹ÚÀ¯¶û | caCORE: A common infrastructure for cancer informatics | ||
| 31 | ±è±â¿ø | Prediction of regulatory networks: genome-wide identification of transcription factor targets from gene expression data | ||
| 31 | ±èÁöÈÆ(H) | EVALUATION AND COMPARISON OF CLUSTERING ALGORITHMS IN ANGLYZING ES CELL GENE EXPRESSION DATA | ||