iRSpot-DACC: a computational predictor for recombination hot/cold spots identification based on dinucleotide-based auto-cross covariance

scientific article published on 19 September 2016

iRSpot-DACC: a computational predictor for recombination hot/cold spots identification based on dinucleotide-based auto-cross covariance is …
instance of (P31):
scholarly articleQ13442814

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P356DOI10.1038/SREP33483
P932PMC publication ID5027590
P698PubMed publication ID27641752

P2093author name stringBin Liu
Xiaolong Wang
Yumeng Liu
Bingquan Liu
Xiaopeng Jin
P2860cites workIdentification of DNA-binding proteins by combining auto-cross covariance transformation and ensemble learningQ50459796
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Recombination spots prediction using DNA physical properties in the saccharomyces cerevisiae genomeQ57272917
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Support vector machine for classification of meiotic recombination hotspots and coldspots in Saccharomyces cerevisiae based on codon compositionQ33241196
Human SNP variability and mutation rate are higher in regions of high recombinationQ34750287
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The influence of recombination on human genetic diversityQ35048296
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RF-DYMHC: detecting the yeast meiotic recombination hotspots and coldspots by random forest model using gapped dinucleotide composition featuresQ35914186
Variation in human meiotic recombinationQ35918568
Identification and analysis of the N(6)-methyladenosine in the Saccharomyces cerevisiae transcriptomeQ36032178
iMiRNA-SSF: Improving the Identification of MicroRNA Precursors by Combining Negative Sets with Different DistributionsQ36453371
iRSpot-PseDNC: identify recombination spots with pseudo dinucleotide compositionQ36740900
Recombination spot identification Based on gapped k-mersQ36748392
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Prediction of midbody, centrosome and kinetochore proteins based on gene ontology informationQ38504965
iRSpot-EL: identify recombination spots with an ensemble learning approachQ39484248
iEnhancer-2L: a two-layer predictor for identifying enhancers and their strength by pseudo k-tuple nucleotide compositionQ40420289
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P275copyright licenseCreative Commons Attribution 4.0 InternationalQ20007257
P6216copyright statuscopyrightedQ50423863
P407language of work or nameEnglishQ1860
P304page(s)33483
P577publication date2016-09-19
P1433published inScientific ReportsQ2261792
P1476titleiRSpot-DACC: a computational predictor for recombination hot/cold spots identification based on dinucleotide-based auto-cross covariance
P478volume6

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cites work (P2860)
Q47173127BioSeq-Analysis: a platform for DNA, RNA and protein sequence analysis based on machine learning approaches
Q61449600Identifying Plant Pentatricopeptide Repeat Coding Gene/Protein Using Mixed Feature Extraction Methods
Q64997830Meta-4mCpred: A Sequence-Based Meta-Predictor for Accurate DNA 4mC Site Prediction Using Effective Feature Representation.
Q47953719iMulti-HumPhos: a multi-label classifier for identifying human phosphorylated proteins using multiple kernel learning based support vector machines.
Q52651537iRSpot-PDI: Identification of recombination spots by incorporating dinucleotide property diversity information into Chou's pseudo components.
Q55513264iRSpot-Pse6NC: Identifying recombination spots in Saccharomyces cerevisiae by incorporating hexamer composition into general PseKNC.
Q57929342iRSpot-SF: Prediction of recombination hotspots by incorporating sequence based features into Chou's Pseudo components

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