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Titlebook: Computational Medicine; Tools and Challenges Zlatko Trajanoski Book 2012 Springer-Verlag Wien 2012 computational medicine

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樓主: Taylor
31#
發(fā)表于 2025-3-26 23:00:45 | 只看該作者
Lipidomics, Mass Spectrometry, and Bioinformatics,racting enormous interest in science, since it delivers information complementary to genomics and proteomics. This uptrend was triggered by progress in mass spectrometry; however, the burgeoning of lipidomics as a major area of research started relatively late compared to that of proteomics. A major
32#
發(fā)表于 2025-3-27 03:38:17 | 只看該作者
,Protein Sequence–Structure–Function–Network Links Discovered with the ANNOTATOR Software Suite: Appat can be translated into protein sequences. This review considers the different concepts applicable to sequence analysis and function prediction of globular and non-globular protein segments. The publicly accessible ANNOTATOR software environment integrates most of the reliable protein sequence-bas
33#
發(fā)表于 2025-3-27 08:04:01 | 只看該作者
3D Structure and Drug Design,vel lead compounds and drugs and in the characterization of the biochemical mechanisms underlying the pharmacological and biological activity. Given that this information driven process is grounded on the experimental or computational determinations of the 3D structures, this chapter begins with a d
34#
發(fā)表于 2025-3-27 10:40:28 | 只看該作者
Integrating Biomolecular and Clinical Data for Cancer Research: Concepts and Challenges,ht the various sources for generating data with specific focus on medium- and large-scale omics approaches as well as relevant public databases. We then give an overview of the computational methods necessary to analyze primary data as well as bioinformatics tools for using databases, extracting pat
35#
發(fā)表于 2025-3-27 14:01:36 | 只看該作者
Applied Data Mining: From Biomarker Discovery to Decision Support Systems,tudy design consideration and bioanalytic concepts for generating biomedical data, followed by various data mining and information retrieval procedures such as feature selection, classification as well as statistical and clinical validation. The reviewed methods are illustrated by real examples from
36#
發(fā)表于 2025-3-27 21:23:01 | 只看該作者
Network-Based Methods for Computational Diagnostics by Means of R,conductor have emerged as a standard research environment to investigate and analyze high-throughput data. Therefore, we present and discuss existing packages, available in R or Bioconductor, that provide methods for . by means of networks. In particular, we summarize packages to reconstruct and ana
37#
發(fā)表于 2025-3-27 23:07:10 | 只看該作者
-art IT solutions for application in medicine.Written by a e.Computational methodologies and modeling play a growing role for investigating mechanisms, and for the diagnosis and therapy of human diseases. This progress gave rise to computational medicine, an interdisciplinary field at the interface
38#
發(fā)表于 2025-3-28 05:05:53 | 只看該作者
Book 2012progress gave rise to computational medicine, an interdisciplinary field at the interface of computer science and medicine. The main focus of computational medicine lies in the development of data analysis methods and mathematical modeling as well as computational simulation techniques specifically
39#
發(fā)表于 2025-3-28 07:55:23 | 只看該作者
,Protein Sequence–Structure–Function–Network Links Discovered with the ANNOTATOR Software Suite: Apped function prediction methods, protein domain databases and pathway, and protein–protein interaction collections developed in academia. As application example, the structural and functional domains of mel-28/ELYS, an important nuclear protein, are delineated and are proposed for experimental follow-up in structural biology and functional studies.
40#
發(fā)表于 2025-3-28 10:36:37 | 只看該作者
Applied Data Mining: From Biomarker Discovery to Decision Support Systems, preclinical and clinical studies, and the application in medical decision making is discussed. This chapter is anticipated to address to those with a bioinformatics background as well as biomedical researchers who are interested in the application of computational methods in biomarker discovery and medical decision making.
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