Association Analysis Techniques and Applications in Bioinformatics
Advances in experimental technologies have given rise to tremendous amounts of biology data. This not only offers valuable sources of data to help understand biological evolution and functional mechanisms, but also poses challenges for accurate and effective data analysis. This book offers an essent...
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| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Lenguaje: | inglés |
| Publicado: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2024.
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| Edición: | 1st ed. 2024. |
| Materias: | |
| Acceso en línea: | https://doi.org/10.1007/978-981-99-8251-6 |
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Tabla de Contenidos:
- Chapter1:Computer science for Molecular biology
- Chapter2:Introduction to association analysis
- Chapter3:Introduction to computational linguistics and biology structure
- Chapter4:Matrix decomposition for dimensionality deduction
- Chapter5:Discovering conserved RNA secondary structures with structure similarity
- Chapter6:Gene ontology for non-coding RNAs classification
- Chapter7:Learning frequent sub-structure by graph mining
- Chapter8:Editing distance and its application to biology graph analytics
- Chapter9:Sequence assembly and applications
- Chapter10:Classifying protein structures by measuring structural similarity
- Chapter11:Identification of metabolic pathways with embedding network
- Chapter12:Emerging Knowledge integration-based approach with multi-sources data for bioinformatics
- Chapter13:Conclusion and Future Work.