Linking, Literature, Information, and Knowledge for Biologie: Workshop of the BioLINK Special Interest Group, ISBM ECCB 2009, Stockholm, June 28-29,
معرفی کتاب «Linking, Literature, Information, and Knowledge for Biologie: Workshop of the BioLINK Special Interest Group, ISBM ECCB 2009, Stockholm, June 28-29,» نوشتهٔ Hagit Shatkay, Christian Blaschke، منتشرشده توسط نشر LNCS در سال 2010. این کتاب در فرمت pdf، زبان انگلیسی ارائه شده است.
This volume of Lecture Notes in Bioinformatics contains selected papers from the workshop of the BioLINK Special Interest Group (SIG) on Linking Literature, Information and Knowledge for Biology. The workshop was held June 28- 29, 2009 at the ISMB/ECCB 2009 conference in Stockholm. About BioLINK......Page 1 History of BioLINK Meetings......Page 3 References......Page 6 Introduction......Page 8 Cell Segmentation......Page 9 Supervised Classification......Page 10 Shape Analysis......Page 11 Subcellular Pattern Unmixing......Page 12 Publicly Available Databases and Analysis of Large Datasets......Page 13 References......Page 15 Introduction......Page 19 Panel Discussion......Page 21 Introduction......Page 23 Overview......Page 24 Figure Splitting......Page 25 ``Ghost'' Detection......Page 26 Panel Type Classification......Page 27 Subcellular Location Pattern Classification......Page 28 Topic Discovery......Page 29 Discussion......Page 30 References......Page 31 Introduction......Page 33 Dataset Construction......Page 34 Methods and Classification......Page 36 Experiments and Results......Page 37 References......Page 41 Introduction......Page 43 Training and Test Set Construction......Page 45 Metadata Protein Tagger......Page 46 Protein Complex Resolver......Page 47 Results......Page 48 Gold Standard Entity Identification (GSEI) Analysis......Page 49 Discussion and Future Work......Page 50 References......Page 51 Introduction......Page 53 Background......Page 54 Integrated Database with Semantic Relations and Microarray Results......Page 55 Discovery Patterns for Novel Hypotheses Generation......Page 56 Evaluation......Page 57 Generating Novel Hypotheses for Potential Therapeutic Agents......Page 58 References......Page 60 Introduction......Page 62 Background and Related Work......Page 63 Data Acquisition......Page 64 Machine Learning Algorithms......Page 65 Results and Discussions......Page 66 Conclusion and Future Direction......Page 68 References......Page 69 Introduction......Page 71 Related Work......Page 72 CBR-Tagger......Page 73 ML-Normalization......Page 74 Results......Page 77 Discussion......Page 78 References......Page 79
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