About: Alignment-free sequence analysis

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In bioinformatics, alignment-free sequence analysis approaches to molecular sequence and structure data provide alternatives over alignment-based approaches. The emergence and need for the analysis of different types of data generated through biological research has given rise to the field of bioinformatics. Molecular sequence and structure data of DNA, RNA, and proteins, gene expression profiles or microarray data, metabolic pathway data are some of the major types of data being analysed in bioinformatics. Among them sequence data is increasing at the exponential rate due to advent of next-generation sequencing technologies. Since the origin of bioinformatics, sequence analysis has remained the major area of research with wide range of applications in database searching, genome annotation

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rdfs:label	Alignment-free sequence analysis (en)
rdfs:comment	In bioinformatics, alignment-free sequence analysis approaches to molecular sequence and structure data provide alternatives over alignment-based approaches. The emergence and need for the analysis of different types of data generated through biological research has given rise to the field of bioinformatics. Molecular sequence and structure data of DNA, RNA, and proteins, gene expression profiles or microarray data, metabolic pathway data are some of the major types of data being analysed in bioinformatics. Among them sequence data is increasing at the exponential rate due to advent of next-generation sequencing technologies. Since the origin of bioinformatics, sequence analysis has remained the major area of research with wide range of applications in database searching, genome annotation (en)
sameAs	Alignment-free sequence analysis
dbp:wikiPageUsesTemplate	dbt:Cite_journal dbt:Not_a_typo dbt:Reflist
Subject	Bioinformatics Computational biology
Link from a Wikipage to an external page	https://usm.github.io https://web.archive.org/web/20140109135217/http:/www.herbbol.org:8000/agp http://acb.qfab.org/acb/decaf+py/ http://bioinfo.net.in/RTD/home.html http://bioinformatics.ua.pt/software/smash/ http://comet.lih.lu/ http://ddg-pharmfac.net/AllergenFP/ http://fswm.gobics.de/ http://github.com/pratas/falcon http://gscompare.ehu.eus/ http://guanine.evolbio.mpg.de/alfy/ http://kmacs.gobics.de/ http://spaced.gobics.de/ http://tlife.fudan.edu.cn/cvtree/ https://www.qiagenbioinformatics.com/products/clc-microbial-genomics-module/ https://yadamp.unisa.it/PROTCOMP http://sourceforge.net/projects/ffp-phylogeny/ http://sourceforge.net/projects/ksnp/ https://github.com/cobilab/eagle https://github.com/jschellh/ProtSpaM https://github.com/smortezah/smashpp https://github.com/yhg926/co-phylog https://code.google.com/p/d2-tools/ http://github.com/DerrickWood/kraken2 http://guanine.evolbio.mpg.de/rush/
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Wikipage page ID	40646055 (xsd:integer)
page length (characters) of wiki page	56039 (xsd:nonNegativeInteger)
Wikipage revision ID	1068561133 (xsd:integer)
Link from a Wikipage to another Wikipage	Protein Suffix tree Rosalind (education platform) Semantic similarity Sequence alignment Sequence analysis Bioinformatics Computational biology Gene expression Gene mapping Gene prediction Genome skimming Distance matrix Jensen–Shannon divergence Lempel–Ziv complexity Metabolic pathway Metagenomics Mutation Mutual information Phylogenetical Phylogenomics Population genetics Chaos game D-na DNA annotation Comparative genomics Computer science Cosine similarity Microarray Information distance Information theory MapReduce Molecular phylogenetics Pearson correlation coefficient UPGMA Variance Euclidean distance Standard deviation Jaccard index Kolmogorov complexity Longest common substring problem Markov model Massive parallel sequencing Mean Multiple sequence alignment Neighbor joining RNA Recombination detection program Similarity measure Single-nucleotide polymorphism dbr:Correction_term dbr:Information_correlation
has abstract	In bioinformatics, alignment-free sequence analysis approaches to molecular sequence and structure data provide alternatives over alignment-based approaches. The emergence and need for the analysis of different types of data generated through biological research has given rise to the field of bioinformatics. Molecular sequence and structure data of DNA, RNA, and proteins, gene expression profiles or microarray data, metabolic pathway data are some of the major types of data being analysed in bioinformatics. Among them sequence data is increasing at the exponential rate due to advent of next-generation sequencing technologies. Since the origin of bioinformatics, sequence analysis has remained the major area of research with wide range of applications in database searching, genome annotation, comparative genomics, molecular phylogeny and gene prediction. The pioneering approaches for sequence analysis were based on sequence alignment either global or local, pairwise or multiple sequence alignment. Alignment-based approaches generally give excellent results when the sequences under study are closely related and can be reliably aligned, but when the sequences are divergent, a reliable alignment cannot be obtained and hence the applications of sequence alignment are limited. Another limitation of alignment-based approaches is their computational complexity and are time-consuming and thus, are limited when dealing with large-scale sequence data. The advent of next-generation sequencing technologies has resulted in generation of voluminous sequencing data. The size of this sequence data poses challenges on alignment-based algorithms in their assembly, annotation and comparative studies. (en)
foaf:isPrimaryTopicOf	http://en.wikipedia.org/wiki/Alignment-free_sequence_analysis
is Link from a Wikipage to another Wikipage of	Genome skimming Genomic signature K-mer Comparative genomics List of bioinformatics software Multiple sequence alignment
is foaf:primaryTopic of	http://en.wikipedia.org/wiki/Alignment-free_sequence_analysis

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