Data Mining for Systems Biology: Methods and Protocols

ISBN-13: 9781493993260 / Angielski / Miękka / 2019 / 243 str.

Hiroshi Mamitsuka

Spis treści

1. Identifying Bacterial Strains from Sequencing Data

            Tommi Mäklin, Jukka Corander, and Antti Honkela

 

2. MetaVW: Large-Scale Machine Learning for Metagenomics Sequence Classification

            Kévin Vervier, Pierre Mahé, and Jean-Philippe Vert

 

3. Online Interactive Microbial Classification and Geospatial Distributional Analysis Using BioAtlas

            Jesper Lund, Qihua Tan, and Jan Baumbach

 

4. Generative Models for Quantification of DNA Modifications

            Tarmo Äijö, Richard Bonneau, and Harri Lähdesmäki

 

5. DiMmer: Discovery of Differentially Methylated Regions in Epigenome-Wide Association Study (EWAS) Data

            Tobias Frisch, Jonatan Gøttcke, Richard Röttger, Qihua Tan, and Jan Baumbach

 

6. Implementing a Transcription Factor Interaction Prediction System Using the GenoMetric Query Language

            Stefano Perna, Arif Canakoglu, Pietro Pinoli, Stefano Ceri, and Limsoon Wong

 

7. Multiple Testing Tool to Detect Combinatorial Effects in Biology

            Aika Terada and Koji Tsuda

 

8. SiBIC: A Tool for Generating a Network of Biclusters Captured by Maximal Frequent Itemset Mining

            Kei-ichiro Takahashi, David A. duVerle, Sohiya Yotsukura, Ichigaku Takigawa, and Hiroshi Mamitsuka

 

9. Computing and Visualizing Gene Function Similarity and Coherence with NaviGO

            Ziyun Ding, Qing Wei, and Daisuke Kihara

 

10. Analyzing Glycan Binding Profiles Using Weighted Multiple Alignment of Trees

            Kiyoko F. Aoki-Kinoshita

 

11. Analysis of Fluxomic Experiments with Principal Metabolic Flux Mode Analysis

            Sahely Bhadra and Juho Rousu

 

12. Analyzing Tandem Mass Spectra Using the DRIP Toolkit: Training, Searching, and Post-Processing

            John T. Halloran

 

13. Sparse Modeling to Analyze Drug-Target Interaction Networks

            Yoshihiro Yamanishi

 

14. DrugE-Rank: Predicting Drug-Target Interactions by Learning to Rank

            Jieyao Deng, Qingjun Yuan, Hiroshi Mamitsuka, and Shanfeng Zhu

 

15. MeSHLabeler and DeepMeSH: Recent Progress in Large-Scale MeSH Indexing

            Shengwen Peng, Hiroshi Mamitsuka, and Shanfeng Zhu

 

16. Disease Gene Classification with Metagraph Representations

            Sezin Kircali Ata, Yuan Fang, Min Wu, Xiao-Li Li, and Xiaokui Xiao

 

17. Inferring Antimicrobial Resistance from Pathogen Genomes in KEGG

            Minoru Kanehisa

Blurb

This fully updated book collects numerous data mining techniques, reflecting the acceleration and diversity of the development of data-driven approaches to the life sciences. The first half of the volume examines genomics, particularly metagenomics and epigenomics, which promise to deepen our knowledge of genes and genomes, while the second half of the book emphasizes metabolism and the metabolome as well as relevant medicine-oriented subjects. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and expert implementation advice that is useful for getting optimal results. 

Authoritative and practical, Data Mining for Systems Biology: Methods and Protocols, Second Edition serves as an ideal resource for researchers of biology and relevant fields, such as medical, pharmaceutical, and agricultural sciences, as well as for the scientists and engineers who are working on developing data-driven techniques, such as databases, data sciences, data mining, visualization systems, and machine learning or artificial intelligence that now are central to the paradigm-altering discoveries being made with a higher frequency.