scholarly article | Q13442814 |
P2093 | author name string | Bin Liu | |
Xiaolong Wang | |||
Yumeng Liu | |||
Bingquan Liu | |||
Xiaopeng Jin | |||
P2860 | cites work | Identification of DNA-binding proteins by combining auto-cross covariance transformation and ensemble learning | Q50459796 |
iRNA-Methyl: Identifying N(6)-methyladenosine sites using pseudo nucleotide composition. | Q50567651 | ||
Enhanced Protein Fold Prediction Method Through a Novel Feature Extraction Technique. | Q50859780 | ||
Using weighted features to predict recombination hotspots in Saccharomyces cerevisiae. | Q50888252 | ||
Protein remote homology detection by combining Chou's distance-pair pseudo amino acid composition and principal component analysis. | Q50927764 | ||
PseKNC: a flexible web server for generating pseudo K-tuple nucleotide composition. | Q51094090 | ||
Predicting protein interaction sites from residue spatial sequence profile and evolution rate. | Q51957448 | ||
A constructive approach for finding arbitrary roots of polynomials by neural networks. | Q51988811 | ||
On lines and planes of closest fit to systems of points in space | Q55877462 | ||
Recombination spots prediction using DNA physical properties in the saccharomyces cerevisiae genome | Q57272917 | ||
Patterns of meiotic double-strand breakage on native and artificial yeast chromosomes | Q64389323 | ||
GC-content evolution in mammalian genomes: the biased gene conversion hypothesis | Q24542511 | ||
High-resolution mapping of meiotic crossovers and non-crossovers in yeast | Q27938210 | ||
nDNA-Prot: identification of DNA-binding proteins based on unbalanced classification. | Q30366530 | ||
A new taxonomy-based protein fold recognition approach based on autocross-covariance transformation. | Q30380129 | ||
PseKNC-General: a cross-platform package for generating various modes of pseudo nucleotide compositions | Q30459140 | ||
Independent component analysis-based penalized discriminant method for tumor classification using gene expression data | Q31041309 | ||
Support vector machine for classification of meiotic recombination hotspots and coldspots in Saccharomyces cerevisiae based on codon composition | Q33241196 | ||
Human SNP variability and mutation rate are higher in regions of high recombination | Q34750287 | ||
An approach for identifying cytokines based on a novel ensemble classifier. | Q34985609 | ||
The influence of recombination on human genetic diversity | Q35048296 | ||
Global mapping of meiotic recombination hotspots and coldspots in the yeast Saccharomyces cerevisiae | Q35287931 | ||
Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequences | Q35810290 | ||
RF-DYMHC: detecting the yeast meiotic recombination hotspots and coldspots by random forest model using gapped dinucleotide composition features | Q35914186 | ||
Variation in human meiotic recombination | Q35918568 | ||
Identification and analysis of the N(6)-methyladenosine in the Saccharomyces cerevisiae transcriptome | Q36032178 | ||
iMiRNA-SSF: Improving the Identification of MicroRNA Precursors by Combining Negative Sets with Different Distributions | Q36453371 | ||
iRSpot-PseDNC: identify recombination spots with pseudo dinucleotide composition | Q36740900 | ||
Recombination spot identification Based on gapped k-mers | Q36748392 | ||
Clustering of meiotic double-strand breaks on yeast chromosome III | Q36769301 | ||
Prediction of midbody, centrosome and kinetochore proteins based on gene ontology information | Q38504965 | ||
iRSpot-EL: identify recombination spots with an ensemble learning approach | Q39484248 | ||
iEnhancer-2L: a two-layer predictor for identifying enhancers and their strength by pseudo k-tuple nucleotide composition | Q40420289 | ||
Identification of microRNA precursor with the degenerate K-tuple or Kmer strategy | Q41952252 | ||
miRClassify: an advanced web server for miRNA family classification and annotation. | Q45957817 | ||
Sequence-dependent prediction of recombination hotspots in Saccharomyces cerevisiae. | Q45961373 | ||
A constructive hybrid structure optimization methodology for radial basis probabilistic neural networks | Q46215307 | ||
P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
P6216 | copyright status | copyrighted | Q50423863 |
P407 | language of work or name | English | Q1860 |
P304 | page(s) | 33483 | |
P577 | publication date | 2016-09-19 | |
P1433 | published in | Scientific Reports | Q2261792 |
P1476 | title | iRSpot-DACC: a computational predictor for recombination hot/cold spots identification based on dinucleotide-based auto-cross covariance | |
P478 | volume | 6 |
Q47173127 | BioSeq-Analysis: a platform for DNA, RNA and protein sequence analysis based on machine learning approaches |
Q61449600 | Identifying Plant Pentatricopeptide Repeat Coding Gene/Protein Using Mixed Feature Extraction Methods |
Q64997830 | Meta-4mCpred: A Sequence-Based Meta-Predictor for Accurate DNA 4mC Site Prediction Using Effective Feature Representation. |
Q47953719 | iMulti-HumPhos: a multi-label classifier for identifying human phosphorylated proteins using multiple kernel learning based support vector machines. |
Q52651537 | iRSpot-PDI: Identification of recombination spots by incorporating dinucleotide property diversity information into Chou's pseudo components. |
Q55513264 | iRSpot-Pse6NC: Identifying recombination spots in Saccharomyces cerevisiae by incorporating hexamer composition into general PseKNC. |
Q57929342 | iRSpot-SF: Prediction of recombination hotspots by incorporating sequence based features into Chou's Pseudo components |
Search more.