The eight papers in this special section were presented at the 7th National conference on bioinformatics and systems Biology of China in 2016. The conference is the most influential conference of the Chinese scientifi...
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The eight papers in this special section were presented at the 7th National conference on bioinformatics and systems Biology of China in 2016. The conference is the most influential conference of the Chinese scientific community of bioinformatics and systems biology.
fuzzy. Fuzzy set theory and fuzzy logic are ideal frameworks for describing some biological systems/objects and providing suitable computational methods for a widely range of bioinformatics problems. In this paper, we...
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ISBN:
(纸本)9780780394889
fuzzy. Fuzzy set theory and fuzzy logic are ideal frameworks for describing some biological systems/objects and providing suitable computational methods for a widely range of bioinformatics problems. In this paper, we present two examples of using fuzzy set theory in bioinformatics, one in fuzzy measurement of ontological similarity and its application in bioinformatics, and the other in the application of the fuzzy k-nearest neighbor algorithm in protein secondary structure prediction. I We also review other "fuzzy" methods for bioinformatics applications.
Cutting-edge biological and bioinformatics research seeks a systems perspective through the analysis of multiple types of high-throughput and other experimental data for the same sample. systems-level analysis require...
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ISBN:
(纸本)0769523447
Cutting-edge biological and bioinformatics research seeks a systems perspective through the analysis of multiple types of high-throughput and other experimental data for the same sample. systems-level analysis requires the integration and fusion of such data, typically through advanced statistics and mathematics. Visualization is a complementary computational approach that supports integration and analysis of complex data or its derivatives. We present a bioinformatics visualization prototype, Juxter, which depicts categorical information derived from or assigned to these diverse data for the purpose of comparing patterns across categorizations. The visualization allows users to easily, discern correlated and anomalous patterns in the data. These patterns, which might not be detected automatically by, algorithms, may, reveal valuable information leading to insight and discovery. We describe the visualization and interaction capabilities and demonstrate its utility in a new field, metagenomics, which combines molecular biology and genetics to identify and characterize genetic material from multi-species microbial samples.
The paper introduces the knowledge engineering (KE) approach for the modeling and the discovery of new knowledge in bioinformatics. This approach extends the machine learning approach with various rule extraction and ...
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ISBN:
(纸本)0780382781
The paper introduces the knowledge engineering (KE) approach for the modeling and the discovery of new knowledge in bioinformatics. This approach extends the machine learning approach with various rule extraction and other knowledge representation procedures. Examples of the KE approach, and especially of one of the recently developed techniques - evolving connectionist systems (ECOS), to challenging problems in bioinformatics are given, that include: DNA sequence analysis, microarray gene expression profiling, protein structure prediction, finding gene regulatory networks, medical prognostic systems, computational neurogenetic modeling.
In this paper research in the field of application multiprocessor systems for genome assemblies reconciliation has been carried out. A large number of algorithmic approaches aimed to solve the task of de novo assembly...
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ISBN:
(纸本)9781467367981
In this paper research in the field of application multiprocessor systems for genome assemblies reconciliation has been carried out. A large number of algorithmic approaches aimed to solve the task of de novo assembly from short reads, however the results of their work on the same raw data often differ essentially. A parallel algorithm for merging two or more assemblies without relying on a reference genome is presented. Due to the large data volume the computations in the distributed memory model on computational cluster are required. The proposed method integrates a combination of draft assemblies reducing resulting contigsfragmentation. Sequential version of the algorithm is implemented in C/C++ and is available at https:***/kromanenkov/gar.
Prediction of a transcription start site (TSS) is one of the many active research areas in bioinformatics. The main purpose of this paper is to study the ability of linear classifiers for predicting a TSS. Also we hav...
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The six papers in this special section were presented at the ieee BIBM 2015 conference that was held in Washington, D.C., November 9-12, 2015. The scientific program highlighted five themes to provide breadth, depth, ...
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The six papers in this special section were presented at the ieee BIBM 2015 conference that was held in Washington, D.C., November 9-12, 2015. The scientific program highlighted five themes to provide breadth, depth, and synergy for research collaboration: 1 genomics and molecular structure, function, and evolution; 2 computationalsystems biology; 3 medical informatics and translational bioinformatics; 4 cross-cutting computational methods and bioinformatics infrastructures; and 5 healthcare informatics,
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