TY  - BOOK
AU  - Priami,Corrado
AU  - Merelli,Emanuela
AU  - Gonzalez,Pablo
AU  - Omicini,Andrea
ED  - SpringerLink (Online service)
TI  - Transactions on Computational Systems Biology III
T2  - Lecture Notes in Computer Science,
SN  - 9783540314462
AV  - QA75.5-76.95 
U1  - 004.0151 23
PY  - 2005///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg
KW  - Computer science
KW  - Database management
KW  - Proteomics
KW  - Bioinformatics
KW  - Computer Science
KW  - Computation by Abstract Devices
KW  - Database Management
N1  - Computer-Aided DNA Base Calling from Forward and Reverse Electropherograms -- A Multi-agent System for Protein Secondary Structure Prediction -- Modeling Kohn Interaction Maps with Beta-Binders: An Example -- Multidisciplinary Investigation into Adult Stem Cell Behavior -- Statistical Model Selection Methods Applied to Biological Networks -- Using Secondary Structure Information to Perform Multiple Alignment -- Frequency Concepts and Pattern Detection for the Analysis of Motifs in Networks -- An Agent-Oriented Conceptual Framework for Systems Biology -- Genetic Linkage Analysis Algorithms and Their Implementation -- Abstract Machines of Systems Biology
N2  - In the last few decades, advances in molecular biology and in the research - frastructure in this ?eld has given rise to the “omics” revolution in molecular biology,alongwiththeexplosionofdatabases:fromgenomicstotranscriptomics, proteomics, interactomics,and metabolomics. However,the huge amount of b- logicalinformationavailablehasleftabottleneckindataprocessing:information over?ow has called for innovative techniques for their visualization, modelling, interpretationandanalysis.The manyresultsfromthe ?eldsofcomputerscience andengineeringhavethenmetwithbiology,leadingto new,emergingdisciplines such as bioinformatics and systems biology. So, for instance, as the result of - plicationoftechniquessuchasmachinelearning,self-organizingmaps,statistical algorithms,clusteringalgorithmsandmulti-agentsystemstomodernbiology,we can actually model and simulate some functions of the cell (e.g., protein inter- tion, gene expression and gene regulation), make inferences from the molecular biology database, make connections among biological data, and derive useful predictions. Today, and more generally, two di?erent scenarios characterize the po- genomic era. On the one hand, the huge amount of datasets made available by biological research all over the world mandates for suitable techniques, tools and methods meant at modelling biological processes and analyzing biological sequences. On the other hand, biological systems work as the sources of a wide range of new computational models and paradigms, which are now ready to be applied in the context of computer-based systems
UR  - http://dx.doi.org/10.1007/11599128
ER  -