Research graph
References from Accurate prediction of RNA 5-hydroxymethylcytosine modification by utilizing novel position-specific gapped k-mer descriptors. Local targets link to admitted publications; unresolved targets remain external evidence.
Nucleoside-5′-phosphates from ribonucleic acid
10.1038/167483a0 · 1951 · External reference
Chemical modifications in the life of an mRNA transcript
10.1146/annurev-genet-120417-031522 · 2018 · External reference
MODOMICS: A database of RNA modification pathways. 2017 update
2017 · External reference
RNA modifications regulating cell fate in cancer
2019 · External reference
The RNA modification landscape in human disease
10.1261/rna.063503.117 · 2017 · External reference
Dynamic RNA modifications in gene expression regulation
10.1016/j.cell.2017.05.045 · 2017 · External reference
10.1016/j.molcel.2019.04.025
10.1016/j.molcel.2019.04.025 · External reference
Genetic control of replication through N1-methyladenine in human cells
2015 · External reference
iRNA-PseU: identifying RNA pseudouridine sites
10.1038/mtna.2016.37 · 2016 · External reference
Bisulfite-free and base-resolution analysis of 5-methylcytidine and 5-hydroxymethylcytidine in RNA with peroxotungstate
2019 · External reference
PACES: prediction of N4-acetylcytidine (ac4C) modification sites in mRNA
2019 · External reference
MM-6mAPred: identifying DNA N6-methyladenine sites based on Markov model
2020 · External reference
10.1021/ja505305z
10.1021/ja505305z · External reference
Effect of light on the nucleotide composition of rRNA of wheat seedlings
10.1007/bf00385075 · 1978 · External reference
Distribution of 5-hydroxymethylcytosine in different human tissues
10.4061/2011/870726 · 2011 · External reference
Transcriptome-wide distribution and function of RNA hydroxymethylcytosine
2016 · External reference
5-hydroxymethylcytosine is detected in RNA from mouse brain tissues
2016 · External reference
iRNA5hmC: the first predictor to identify RNA 5-hydroxymethylcytosine modifications using machine learning
2020 · External reference
A k-mer scheme to predict piRNAs and characterize locust piRNAs
10.1093/bioinformatics/btr016 · 2011 · External reference
10.1016/j.jtbi.2010.12.024
10.1016/j.jtbi.2010.12.024 · External reference
iRNA-m7G: identifying N7-methylguanosine sites by fusing multiple features
10.1016/j.omtn.2019.08.022 · 2019 · External reference
RepDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects
2015 · External reference
Unresolved reference
2008 · External reference
10.1109/cibcb.2008.4675758
10.1109/cibcb.2008.4675758 · External reference
A k-mer-based barcode DNA classification methodology based on spectral representation and a neural gas network
10.1016/j.artmed.2015.06.002 · 2015 · External reference
LncRNA-MFDL: identification of human long non-coding RNAs by fusing multiple features and using deep learning
2015 · External reference
Functional classification of long non-coding RNAs by k-mer content
2018 · External reference
PseUI: Pseudouridine sites identification based on RNA sequence information
2018 · External reference
XG-PseU: an eXtreme gradient boosting based method for identifying pseudouridine sites
2020 · External reference
Transcriptome-wide annotation of m5C RNA modifications using machine learning
2018 · External reference
RNAm 5CPred: prediction of RNA 5-methylcytosine sites based on three different kinds of nucleotide composition
2019 · External reference
Enhanced regulatory sequence prediction using gapped k-mer features
2014 · External reference
PyFeat: a Python-based effective feature generation tool for DNA, RNA and protein sequences
2019 · External reference
LS-GKM: A new gkm-SVM for large-scale datasets
2016 · External reference
GkmExplain: Fast and accurate interpretation of nonlinear gapped k-mer SVMs
10.1093/bioinformatics/btz322 · 2019 · External reference
A linear regression predictor for identifying N6-methyladenosine sites using frequent gapped K-mer pattern
10.1016/j.omtn.2019.10.001 · 2019 · External reference
iPro70-FMWin: identifying Sigma70 promoters using multiple windowing and minimal features
10.1007/s00438-018-1487-5 · 2019 · External reference
Finding sequence motifs with Bayesian models incorporating positional information: an application to transcription factor binding sites
2008 · External reference
CRISPRpred: A flexible and efficient tool for sgRNAs on-target activity prediction in CRISPR/Cas9 systems
2017 · External reference
Amplification of GC-rich genes by following a combination strategy of primer design, enhancers and modified PCR cycle conditions
2007 · External reference
The role of posttranscriptional modification in stabilization of transfer RNA from hyperthermophiles
1994 · External reference
RNA-guided RNA modification: functional organization of the archaeal H/ACA RNP
2005 · External reference
The emerging biology of RNA post-transcriptional modifications
10.1080/15476286.2016.1267096 · 2017 · External reference
Relationships between genomic G+C content, RNA secondary structures, and optimal growth temperature in prokaryotes
10.1007/pl00006186 · 1997 · External reference
Feature selection for classification
1997 · External reference
Classification with correlated features: unreliability of feature ranking and solutions
2011 · External reference
Random forests
10.1023/a:1010933404324 · 2001 · External reference
Classification and regression by randomForest
10.1057/9780230509993 · 2002 · External reference
Using random forest for protein fold prediction problem: An empirical study
2010 · External reference
Data mining in the life science swith random forest: a walk in the park or lost in the jungle?
2013 · External reference
A combination of feature extraction methods with an ensemble of different classifiers for protein structural class prediction problem
10.1109/tcbb.2013.65 · 2013 · External reference
Random forest classifier combined with feature selection for breast cancer diagnosis and prognostic
2013 · External reference
A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data
2009 · External reference
Logistic regression
10.1007/978-1-59745-530-5_14 · 2007 · External reference
Classification of gene microarrays by penalized logistic regression
2004 · External reference
Circulating cell-free DNA: A promising marker of pathologic tumor response in rectal cancer patients receiving preoperative chemoradiotherapy
10.1245/s10434-011-1638-y · 2011 · External reference
Taxonomic use of DNA G+C content and DNA-DNA hybridization in the genomic age
10.1099/ijs.0.056994-0 · 2014 · External reference
Scikit-learn: machine learning in python
2011 · External reference
Generalized Hessian matrix and second-order optimality conditions for problems with C1,1 data
10.1007/bf01442169 · 1984 · External reference
LIUboost: locality informed under-boosting for imbalanced data classification
2019 · External reference
Unresolved reference
2017 · External reference
Cross-validation methods
2000 · External reference
Support-vector networks
10.1023/a:1022627411411 · 1995 · External reference
Fast Gaussian Naïve Bayes for searchlight classification analysis
10.1016/j.neuroimage.2017.09.001 · 2017 · External reference
CFSBoost: cumulative feature subspace boosting for drug-target interaction prediction
10.1016/j.jtbi.2018.12.024 · 2019 · External reference
10.1016/j.ab.2014.04.001
10.1016/j.ab.2014.04.001 · External reference
