Data Mining for Pattern Recognition and Pattern Matching in Bioinformatics

Data Mining for Pattern Recognition and Pattern Matching in Bioinformatics PDF Author: Binod Kumar
Publisher: GRIN Verlag
ISBN: 3346162087
Category : Medical
Languages : en
Pages : 79

Get Book

Book Description
Master's Thesis from the year 2006 in the subject Computer Science - Bioinformatics, , language: English, abstract: Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Data mining tools predict future trends and behaviors allowing businesses to make proactive, knowledge-driven decisions. Data mining tools can answer business questions that traditionally were too time-consuming to resolve. They scour databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectation. Automated pattern matching- the ability of a program to compare known patterns and determine the degree of similarity –forms the basis for automated sequence analysis, modeling of protein structures, locating homologous genes, data mining, Internet search engines etc. in bioinformatics. Data mining relies on algorithm pattern matching to locate patterns in online and local databases, using a variety of technologies, from simple keyword matching to rule based expert system and artificial neural networks. In this dissertation, the basic problems related to pattern reorganization and pattern matching for nucleotide and protein sequence alignment are discussed. The main techniques used to solve these problems and a comprehensive survey of most influential algorithms that were proposed during the last decay is described.

Data Mining for Pattern Recognition and Pattern Matching in Bioinformatics

Data Mining for Pattern Recognition and Pattern Matching in Bioinformatics PDF Author: Binod Kumar
Publisher: GRIN Verlag
ISBN: 3346162087
Category : Medical
Languages : en
Pages : 79

Get Book

Book Description
Master's Thesis from the year 2006 in the subject Computer Science - Bioinformatics, , language: English, abstract: Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Data mining tools predict future trends and behaviors allowing businesses to make proactive, knowledge-driven decisions. Data mining tools can answer business questions that traditionally were too time-consuming to resolve. They scour databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectation. Automated pattern matching- the ability of a program to compare known patterns and determine the degree of similarity –forms the basis for automated sequence analysis, modeling of protein structures, locating homologous genes, data mining, Internet search engines etc. in bioinformatics. Data mining relies on algorithm pattern matching to locate patterns in online and local databases, using a variety of technologies, from simple keyword matching to rule based expert system and artificial neural networks. In this dissertation, the basic problems related to pattern reorganization and pattern matching for nucleotide and protein sequence alignment are discussed. The main techniques used to solve these problems and a comprehensive survey of most influential algorithms that were proposed during the last decay is described.

Sequence Data Mining

Sequence Data Mining PDF Author: Guozhu Dong
Publisher: Springer Science & Business Media
ISBN: 0387699376
Category : Computers
Languages : en
Pages : 160

Get Book

Book Description
Understanding sequence data, and the ability to utilize this hidden knowledge, will create a significant impact on many aspects of our society. Examples of sequence data include DNA, protein, customer purchase history, web surfing history, and more. This book provides thorough coverage of the existing results on sequence data mining as well as pattern types and associated pattern mining methods. It offers balanced coverage on data mining and sequence data analysis, allowing readers to access the state-of-the-art results in one place.

Scalable Pattern Recognition Algorithms

Scalable Pattern Recognition Algorithms PDF Author: Pradipta Maji
Publisher: Springer Science & Business Media
ISBN: 3319056301
Category : Computers
Languages : en
Pages : 316

Get Book

Book Description
This book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The text reviews both established and cutting-edge research, providing a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics. Features: integrates different soft computing and machine learning methodologies with pattern recognition tasks; discusses in detail the integration of different techniques for handling uncertainties in decision-making and efficiently mining large biological datasets; presents a particular emphasis on real-life applications, such as microarray expression datasets and magnetic resonance images; includes numerous examples and experimental results to support the theoretical concepts described; concludes each chapter with directions for future research and a comprehensive bibliography.

Combinatorial Pattern Matching

Combinatorial Pattern Matching PDF Author: Ferdinando Cicalese
Publisher: Springer
ISBN: 3319199293
Category : Computers
Languages : en
Pages : 412

Get Book

Book Description
This book constitutes the refereed proceedings of the 26th Annual Symposium on Combinatorial Pattern Matching, CPM 2015, held on Ischia Island, Italy, in June/July 2015. The 34 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 83 submissions. The papers address issues of searching and matching strings and more complicated patterns such as trees; regular expressions; graphs; point sets; and arrays. The goal is to derive combinatorial properties of such structures and to exploit these properties in order to achieve superior performance for the corresponding computational problems. The meeting also deals with problems in computational biology; data compression and data mining; coding; information retrieval; natural language processing; and pattern recognition.

Combinatorial Pattern Matching

Combinatorial Pattern Matching PDF Author: Alexander S. Kulikov
Publisher: Springer
ISBN: 3319075667
Category : Computers
Languages : en
Pages : 283

Get Book

Book Description
This book constitutes the refereed proceedings of the 25th Annual Symposium on Combinatorial Pattern Matching, CPM 2014, held in Moscow, Russia, in June 2014. The 28 revised full papers presented together with 5 invited talks were carefully reviewed and selected from 54 submissions. The papers address issues of searching and matching strings and more complicated patterns such as trees; regular expressions; graphs; point sets; and arrays. The goal is to derive combinatorial properties of such structures and to exploit these properties in order to achieve superior performance for the corresponding computational problems. The meeting also deals with problems in computational biology; data compression and data mining; coding; information retrieval; natural language processing; and pattern recognition.

Pattern Recognition in Bioinformatics

Pattern Recognition in Bioinformatics PDF Author: Tjeerd M.H. Dijkstra
Publisher: Springer Science & Business Media
ISBN: 364216000X
Category : Science
Languages : en
Pages : 458

Get Book

Book Description
This book constitutes the refereed proceedings of the 5th International Conference on Pattern Recognition in Bioinformatics, PRIB 2010, held in Nijmegen, The Netherlands, in September 2010. The 38 revised full papers presented were carefully reviewed and selected from 46 submissions. The field of bioinformatics has two main objectives: the creation and maintenance of biological databases and the analysis of life sciences data in order to unravel the mysteries of biological function. Computer science methods such as pattern recognition, machine learning, and data mining have a great deal to offer the field of bioinformatics.

Combinatorial Pattern Matching

Combinatorial Pattern Matching PDF Author: Gregory Kucherov
Publisher: Springer
ISBN: 3642024416
Category : Computers
Languages : en
Pages : 370

Get Book

Book Description
This book constitutes the refereed proceedings of the 20th Annual Symposium on Combinatorial Pattern Matching, CPM 2009, held in Lille, France in June 2009. The 27 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 63 submissions. The papers address all areas related to combinatorial pattern matching and its applications, such as coding and data compression, computational biology, data mining, information retrieval, natural language processing, pattern recognition, string algorithms, string processing in databases, symbolic computing and text searching.

Combinatorial Pattern Matching

Combinatorial Pattern Matching PDF Author: Raffaele Giancarlo
Publisher: Springer
ISBN: 3642214584
Category : Computers
Languages : en
Pages : 493

Get Book

Book Description
This book constitutes the refereed proceedings of the 22nd Annual Symposium on Combinatorial Pattern Matching, CPM 2011, held in Palermi, Italy, in June 2011. The 36 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 70 submissions. The papers address issues of searching and matching strings and more complicated patterns such as trees, regular expressions, graphs, point sets, and arrays. The goal is to derive non-trivial combinatorial properties of such structures and to exploit these properties in order to either achieve superior performance for the corresponding computational problems or pinpoint conditions under which searches cannot be performed efficiently. The meeting also deals with problems in computational biology, data compression and data mining, coding, information retrieval, natural language processing and pattern recognition.

Combinatorial Pattern Matching

Combinatorial Pattern Matching PDF Author: Juha Kärkkäinen
Publisher: Springer
ISBN: 3642312659
Category : Computers
Languages : en
Pages : 466

Get Book

Book Description
This book constitutes the refereed proceedings of the 23rd Annual Symposium on Combinatorial Pattern Matching, CPM 2012, held in Helsinki, Finland, in July 2012. The 33 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 60 submissions. The papers address issues of searching and matching strings and more complicated patterns such as trees, regular expressions, graphs, point sets, and arrays. The goal is to derive non-trivial combinatorial properties of such structures and to exploit these properties in order to either achieve superior performance for the corresponding computational problems or pinpoint conditions under which searches cannot be performed efficiently. The meeting also deals with problems in computational biology, data compression and data mining, coding, information retrieval, natural language processing, and pattern recognition.

Combinatorial Pattern Matching

Combinatorial Pattern Matching PDF Author: Paolo Ferragina
Publisher: Springer Science & Business Media
ISBN: 3540690662
Category : Computers
Languages : en
Pages : 327

Get Book

Book Description
This book constitutes the refereed proceedings of the 19th Annual Symposium on Combinatorial Pattern Matching, CPM 2008, held in Pisa, Italy, in June 2008. The 25 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 78 submissions. The papers address all areas related to combinatorial pattern matching and its applications, such as coding and data compression, computational biology, data mining, information retrieval, natural language processing, pattern recognition, string algorithms, string processing in databases, symbolic computing and text searching.