ライフサイエンスコーパス: knowledge discovery

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1 mbedded in scientific literature for further knowledge discovery.

2 protocols in both prediction and biological knowledge discovery.

3 sign, data normalization and true biological knowledge discovery.

4 ne tools for gene similarity measurement and knowledge discovery.

5 hine learning, knowledge representation, and knowledge discovery.

6 abases to support their complex analysis and knowledge discovery.

7 obust and automated method for miRNA related knowledge discovery.

8 ntial of the proposed approach to biomedical knowledge discovery.

9 edical entities from texts into networks for knowledge discovery.

10 ing network data from external databases for knowledge discovery.

11 "Full feature spectrum" knowledge discovery across heterogeneous data sources re

12 cer could greatly support literature review, knowledge discovery and applications in cancer research.

13 tailoring HMM topologies to data for use in knowledge discovery and clustering.

14 enge Evaluation task that we created for the Knowledge Discovery and Data Mining (KDD) Challenge Cup.

15 logy would allow the development of advanced knowledge discovery and data mining tools for across com

16 pted in biomedical research and practice for knowledge discovery and decision support.

17 hop was 'Roles for text mining in biomedical knowledge discovery and translational medicine'.

18 Data-driven knowledge discovery approaches can potentially unveil hi

19 Here we describe KODAMA (knowledge discovery by accuracy maximization), an unsupe

20 ilarity searches, information retrieval, and knowledge discovery by providing the Protein Sequence Da

21 fore feature extraction, data reduction, and knowledge discovery can ensue.

22 hich will be seamlessly integrated forming a knowledge discovery framework.

23 monly used inductive programming methods for knowledge discovery from data assume that the elements o

24 Text mining systems aim at knowledge discovery from text collections.

25 ioinformatics toolkits that will lead to new knowledge discovery from their data.

26 isual analytic platform that will facilitate knowledge discoveries in future network and systems biol

27 e interaction to facilitate novel biological knowledge discoveries in modern plant genomics.

28 We developed and applied a Knowledge Discovery in Databases procedure to analyse me

29 GPS is particularly useful for knowledge discovery in environments with reduced dataset

30 arkers and genes, and it greatly facilitates knowledge discovery in genome-wide SNP scanning experime

31 mining can provide an efficient pathway for knowledge discovery in the next generation of materials

32 tifying by transplant center and using novel knowledge discovery methods.

33 experimental findings here represent, to our knowledge, discovery of a previously undescribed set of

34 sets required for the data analysis in their knowledge discovery process.

35 arious blockade modes for classification and knowledge discovery purposes.

36 nce, and Pearson - and focused on their true knowledge discovery rates in associating pathway genes a

37 of the TM, we made the important new (to our knowledge) discovery that the stiffness of the TM is red

38 ed for innovative information management and knowledge discovery tools to sift through these vast vol

39 ying databases for information retrieval and knowledge discovery, with functionalities for interactiv

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