Computational detection of significant variation in binding affinity across two sets of sequences with application to the analysis of replication origins in yeast

BMC Bioinformatics

Volumn 9, Issue , 2008, Pages

  Keich, Uri ^a   Gao, Hong ^b   Garretson, Jeffrey S ^a   Bhaskar, Anand ^a   Liachko, Ivan ^c   Donato, Justin ^d   Tye, Bik K ^c  

^a Department of Computer Science and School of Operations Research and Information Engineering   (United States)

^b Plant Breeding and Genetics Section in the School of Integrative Plant Science   (United States)

^c Department of Obstetrics Gynecology   (United States)

^d UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BINDING AFFINITIES; BOOTSTRAP APPROACH; COMPUTATIONAL DETECTION; COMPUTATIONAL SOLUTIONS; DNA REPLICATIONS; POSITION WEIGHTS; REPLICATION ORIGIN; RESAMPLING;

BINDING ENERGY; DNA SEQUENCES;

YEAST;

GENE PRODUCT; MINICHROMOSOME MAINTENANCE PROTEIN; MINICHROMOSOME MAINTENANCE PROTEIN 1-1; PROTEIN FKH2; UNCLASSIFIED DRUG; FUNGAL DNA;

ANALYTIC METHOD; ARTICLE; BINDING AFFINITY; BINDING SITE; BOOTSTRAPPING; CHROMATIN; CONTROLLED STUDY; DNA REPLICATION ORIGIN; FUNGUS GROWTH; GENE SEQUENCE; GENE SILENCING; GENETIC VARIABILITY; MUTANT; NONHUMAN; PROBLEM SOLVING; SACCHAROMYCES CEREVISIAE; SIGNIFICANCE ASSESSMENT OF THE DIFFERENCE IN MATRIX MATCHES; STATISTICAL MODEL; ALGORITHM; BIOLOGICAL MODEL; COMPUTER SIMULATION; DNA SEQUENCE; GENETICS; METHODOLOGY; MOLECULAR GENETICS; NUCLEOTIDE SEQUENCE; PROTEIN BINDING; SEQUENCE ALIGNMENT; STATISTICAL ANALYSIS;

SACCHAROMYCES CEREVISIAE;

ALGORITHMS; BASE SEQUENCE; BINDING SITES; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; DNA, FUNGAL; GENETIC VARIATION; MODELS, GENETIC; MOLECULAR SEQUENCE DATA; PROTEIN BINDING; REPLICATION ORIGIN; SACCHAROMYCES CEREVISIAE; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, DNA;

EID: 53849102555     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-9-372     Document Type: Article

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