Research graph
References from AI applications in functional genomics. Local targets link to admitted publications; unresolved targets remain external evidence.
Editorial: A new discipline, a new name, a new journal
10.1016/0888-7543(87)90098-x · 1987 · External reference
Unresolved reference
External reference
Use of the ‘perceptron’ algorithm to distinguish translational initiation sites in e. coli
10.1093/nar/10.9.2997 · 1982 · External reference
Deep learning for computational biology
10.15252/msb.20156651 · 2016 · External reference
10.1093/bib/bbt020
10.1093/bib/bbt020 · External reference
10.1016/j.cell.2018.05.015
10.1016/j.cell.2018.05.015 · External reference
10.1093/bfgp/ely030
10.1093/bfgp/ely030 · External reference
Deep learning for regulatory genomics
10.1038/nbt.3313 · 2015 · External reference
10.1021/acs.jcim.6b00740
10.1021/acs.jcim.6b00740 · External reference
Machine and deep learning meet genome-scale metabolic modeling
10.1371/journal.pcbi.1007084 · 2019 · External reference
Rise of deep learning for genomic, proteomic, and metabolomic data integration in precision medicine
10.1089/omi.2018.0097 · 2018 · External reference
The perceptron: A probabilistic model for information storage and organization in the brain
10.1037/h0042519 · 1958 · External reference
Unresolved reference
External reference
A primer on deep learning in genomics
10.1038/s41588-018-0295-5 · 2018 · External reference
10.1038/s41576-019-0122-6
10.1038/s41576-019-0122-6 · External reference
10.1038/s41591-018-0316-z
10.1038/s41591-018-0316-z · External reference
10.1038/nature14539
10.1038/nature14539 · External reference
The big challenges of big data
10.1038/498255a · 2013 · External reference
Nonlinear principal component analysis using autoassociative neural networks
10.1002/aic.690370209 · 1991 · External reference
Bayesian methods for data analysis
10.1016/j.ajo.2009.11.011 · 2010 · External reference
Support-vector networks
1995 · External reference
Unresolved reference
2014 · External reference
10.1016/j.neunet.2014.09.003
10.1016/j.neunet.2014.09.003 · External reference
10.1162/neco.2006.18.7.1527
10.1162/neco.2006.18.7.1527 · External reference
A learning algorithm for continually running fully recurrent neural networks
10.1162/neco.1989.1.2.270 · 1989 · External reference
Deep Boltzmann machines
2009 · External reference
Gradient-based learning applied to document recognition
10.1109/5.726791 · 1998 · External reference
10.1126/science.1127647
10.1126/science.1127647 · External reference
Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
2010 · External reference
Unresolved reference
External reference
10.1016/j.ymeth.2019.04.008
10.1016/j.ymeth.2019.04.008 · External reference
Deep learning in mining biological data
2021 · External reference
10.1038/nature03001
10.1038/nature03001 · External reference
10.1126/science.274.5287.546
10.1126/science.274.5287.546 · External reference
10.1126/science.278.5338.601
10.1126/science.278.5338.601 · External reference
Deep learning for health informatics
10.1109/jbhi.2016.2636665 · 2016 · External reference
Opportunities and obstacles for deep learning in biology and medicine
10.1098/rsif.2017.0387 · 2018 · External reference
10.1016/j.gpb.2017.07.003
10.1016/j.gpb.2017.07.003 · External reference
Unresolved reference
External reference
10.1038/nbt.4233
10.1038/nbt.4233 · External reference
Deep learning in bioinformatics
2016 · External reference
10.1093/bib/bbx044
10.1093/bib/bbx044 · External reference
Secondary structure prediction of all-helical proteins in two states
10.1093/protein/6.8.831 · 1993 · External reference
10.1093/bioinformatics/bts598
10.1093/bioinformatics/bts598 · External reference
Continuous distributed representation of biological sequences for deep proteomics and genomics
10.1371/journal.pone.0141287 · 2015 · External reference
10.1109/tcbb.2014.2343960
10.1109/tcbb.2014.2343960 · External reference
10.1038/nbt.3300
10.1038/nbt.3300 · External reference
10.1038/nmeth.3547
10.1038/nmeth.3547 · External reference
10.1002/prot.1036
10.1002/prot.1036 · External reference
Linear regression models for solvent accessibility prediction in proteins
10.1089/cmb.2005.12.355 · 2005 · External reference
10.1534/genetics.106.055921
10.1534/genetics.106.055921 · External reference
A robust linear regression based algorithm for automated evaluation of peptide identifications from shotgun proteomics by use of reversed-phase liquid chromatography retention time
10.1186/1471-2105-9-347 · 2008 · External reference
Genomic selection using regularized linear regression models: ridge regression, lasso, elastic net and their extensions
10.1186/1753-6561-6-s2-s10 · 2012 · External reference
Statistical analysis and modeling of mass spectrometry-based metabolomics data
10.1007/978-1-4939-1258-2_22 · 2014 · External reference
Protein secondary structure prediction based on an improved support vector machines approach
10.1093/protein/gzg072 · 2003 · External reference
Unresolved reference
2007 · External reference
Anglor: A composite machine-learning algorithm for protein backbone torsion angle prediction
2008 · External reference
10.1016/j.str.2011.05.004
10.1016/j.str.2011.05.004 · External reference
Recursive SVM biomarker selection for early detection of breast cancer in peripheral blood
10.1186/1755-8794-6-s1-s4 · 2013 · External reference
10.1038/ng.2892
10.1038/ng.2892 · External reference
Unresolved reference
2007 · External reference
Diagnosis of ovarian cancer using decision tree classification of mass spectral data
2003 · External reference
Unresolved reference
2004 · External reference
10.1007/11871637_7
10.1007/11871637_7 · External reference
& Fu, W.A random forest approach to the detection of epistatic interactions in case-control studies
10.1186/1471-2105-10-s1-s65 · 2009 · External reference
10.1016/j.ygeno.2012.04.003
10.1016/j.ygeno.2012.04.003 · External reference
10.1038/nbt.3157
10.1038/nbt.3157 · External reference
10.1101/gr.186401
10.1101/gr.186401 · External reference
Feature subset selection for splice site prediction
10.1093/bioinformatics/18.suppl_2.s75 · 2002 · External reference
Statistical approaches for DNA barcoding
10.1080/10635150500431239 · 2006 · External reference
10.1109/icdm.2009.85
10.1109/icdm.2009.85 · 2009 · External reference
Tmb-hunt: a web server to screen sequence sets for transmembrane beta-barrel proteins
10.1093/nar/gki384 · 2005 · External reference
A regression-based k nearest neighbor algorithm for gene function prediction from heterogeneous data
10.1186/1471-2105-7-s1-s11 · 2006 · External reference
10.1038/tpj.2010.56
10.1038/tpj.2010.56 · External reference
10.1086/425587
10.1086/425587 · External reference
10.1007/s12038-007-0102-4
10.1007/s12038-007-0102-4 · External reference
10.1016/j.jmb.2008.10.018
10.1016/j.jmb.2008.10.018 · External reference
10.1109/bibmw.2011.6112520
10.1109/bibmw.2011.6112520 · External reference
Multivariate analysis in metabolomics. Current
2013 · External reference
Sparse principal component analysis in cancer research
2014 · External reference
Unsupervised segmentation of continuous genomic data
10.1093/bioinformatics/btm096 · 2007 · External reference
10.1093/bioinformatics/btq175
10.1093/bioinformatics/btq175 · External reference
Unsupervised pattern discovery in human chromatin structure through genomic segmentation
10.1038/nmeth.1937 · 2012 · External reference
10.1093/bioinformatics/btu519
10.1093/bioinformatics/btu519 · External reference
Jointly characterizing epigenetic dynamics across multiple human cell types
10.1093/nar/gkw278 · 2016 · External reference
Discriminant analysis and its application in dna sequence motif recognition
10.1093/bib/1.4.331 · 2000 · External reference
10.1016/j.chemolab.2008.04.005
10.1016/j.chemolab.2008.04.005 · External reference
Comparison of linear discriminant analysis methods for the classification of cancer based on gene expression data
10.1186/1756-9966-28-149 · 2009 · External reference
10.1007/0-387-29362-0_13
10.1007/0-387-29362-0_13 · External reference
10.1038/ng1966
10.1038/ng1966 · External reference
Intelligent kernel k-means for clustering gene expression
10.1016/j.procs.2015.07.544 · 2015 · External reference
Clustering algorithms: Their application to gene expression data
10.4137/bbi.s38316 · 2016 · External reference
DeepCpG: accurate prediction of single-cell dna methylation states using deep learning
2017 · External reference
10.1038/s41588-018-0167-z
10.1038/s41588-018-0167-z · External reference
Application of a deep neural network to metabolomics studies and its performance in determining important variables
10.1021/acs.analchem.7b03795 · 2018 · External reference
10.1002/pmic.201900019
10.1002/pmic.201900019 · External reference
10.1093/bioinformatics/btk036
10.1093/bioinformatics/btk036 · External reference
10.1109/artcom.2009.209
10.1109/artcom.2009.209 · 2009 · External reference
10.1109/csndsp16145.2010.5580318
10.1109/csndsp16145.2010.5580318 · External reference
10.5392/ijoc.2013.9.4.011
10.5392/ijoc.2013.9.4.011 · External reference
10.1101/gr.200535.115
10.1101/gr.200535.115 · External reference
Mirtdl: A deep learning approach for mirna target prediction
10.1109/tcbb.2015.2510002 · 2016 · External reference
Protein secondary structure prediction using deep convolutional neural fields
2016 · External reference
Predicting enhancers with deep convolutional neural networks
2016 · External reference
Unresolved reference
External reference
10.1038/s41588-018-0160-6
10.1038/s41588-018-0160-6 · External reference
10.1016/j.ymeth.2019.03.020
10.1016/j.ymeth.2019.03.020 · External reference
10.1016/j.knosys.2016.11.015
10.1016/j.knosys.2016.11.015 · External reference
10.1101/103994
10.1101/103994 · External reference
Recurrent neural network for predicting transcription factor binding sites
10.1038/s41598-018-33321-1 · 2018 · External reference
Detection of dna base modifications by deep recurrent neural network on oxford nanopore sequencing data
2019 · External reference
Long short-term memory
10.1162/neco.1997.9.8.1735 · 1997 · External reference
Unresolved reference
External reference
Convolutional LSTM networks for subcellular localization of proteins
2015 · External reference
DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of dna sequences
10.1093/nar/gkw226 · 2016 · External reference
Unresolved reference
2017 · External reference
10.1109/compsac.2019.10204
10.1109/compsac.2019.10204 · External reference
Epigenome-based splicing prediction using a recurrent neural network
2020 · External reference
10.1109/bibe.2004.1317394
10.1109/bibe.2004.1317394 · 2004 · External reference
Protein function prediction using deep restricted boltzmann machines
2017 · External reference
10.1093/bioinformatics/btx408
10.1093/bioinformatics/btx408 · External reference
Deep learning methods for protein torsion angle prediction
2017 · External reference
Deep Boltzmann machine based breast cancer risk detection for healthcare systems
2018 · External reference
Unresolved reference
2014 · External reference
Unresolved reference
2016 · External reference
Breast cancer classification using deep belief networks
10.1016/j.eswa.2015.10.015 · 2016 · External reference
10.1088/1742-6596/835/1/012003
10.1088/1742-6596/835/1/012003 · External reference
A new method for enhancer prediction based on deep belief network
2017 · External reference
Discriminative deep belief networks for microarray based cancer classification
2017 · External reference
10.1145/2649387.2649442
10.1145/2649387.2649442 · 2014 · External reference
10.1016/j.cels.2017.06.003
10.1016/j.cels.2017.06.003 · External reference
10.1016/j.gpb.2018.08.003
10.1016/j.gpb.2018.08.003 · External reference
10.1101/318295
10.1101/318295 · External reference
Methylnet: an automated and modular deep learning approach for dna methylation analysis
2020 · External reference
Unresolved reference
External reference
Unresolved reference
External reference
Low-dose ct image denoising using a generative adversarial network with wasserstein distance and perceptual loss
10.1109/tmi.2018.2827462 · 2018 · External reference
10.1038/s42256-019-0017-4
10.1038/s42256-019-0017-4 · External reference
10.1093/bioinformatics/btz317
10.1093/bioinformatics/btz317 · External reference
Realistic in silico generation and augmentation of single-cell rna-seq data using generative adversarial networks
10.1038/s41467-019-14018-z · 2020 · External reference
Genome: twisting stories with dna
10.1016/j.endeavour.2013.05.003 · 2013 · External reference
10.1038/290457a0
10.1038/290457a0 · External reference
10.1126/science.7542800
10.1126/science.7542800 · External reference
Dna sequencing with chain-terminating inhibitors
10.1073/pnas.74.12.5463 · 1977 · External reference
10.1038/265687a0
10.1038/265687a0 · External reference
10.1016/j.ygeno.2015.11.003
10.1016/j.ygeno.2015.11.003 · External reference
10.1038/nature03959
10.1038/nature03959 · External reference
10.1038/nature07517
10.1038/nature07517 · External reference
10.1073/pnas.0230489100
10.1073/pnas.0230489100 · External reference
10.1016/j.nantod.2012.12.008
10.1016/j.nantod.2012.12.008 · External reference
10.1080/14772000.2015.1099575
10.1080/14772000.2015.1099575 · External reference
10.1038/nrg3920
10.1038/nrg3920 · External reference
10.1016/0022-2836(90)90223-9
10.1016/0022-2836(90)90223-9 · External reference
10.1038/nature04979
10.1038/nature04979 · External reference
10.1038/s41588-021-00782-6
10.1038/s41588-021-00782-6 · External reference
Deep learning in clinical natural language processing: a methodical review
2020 · External reference
Pretraining model for biological sequence data
2021 · External reference
Unresolved reference
2013 · External reference
Attention is all you need
2017 · External reference
Unresolved reference
2019 · External reference
16s rRNA sequence embeddings: Meaningful numeric feature representations of nucleotide sequences that are convenient for downstream analyses
10.1371/journal.pcbi.1006721 · 2019 · External reference
Immune2vec: Embedding b/t cell receptor sequences in RN, using natural language processing
10.3389/fimmu.2021.680687 · 2021 · External reference
10.1093/bib/bbab005
10.1093/bib/bbab005 · External reference
10.1038/nrg3404
10.1038/nrg3404 · External reference
10.1126/science.1180823
10.1126/science.1180823 · External reference
10.1126/science.aaf1420
10.1126/science.aaf1420 · External reference
10.1038/ng.846
10.1038/ng.846 · External reference
10.1016/j.cels.2016.02.003
10.1016/j.cels.2016.02.003 · External reference
10.1038/nmeth.4627
10.1038/nmeth.4627 · External reference
10.1371/journal.pcbi.1005807
10.1371/journal.pcbi.1005807 · External reference
Deepcrispr: optimized crispr guide rna design by deep learning
10.1186/s13059-018-1459-4 · 2018 · External reference
10.1093/bioinformatics/btab268
10.1093/bioinformatics/btab268 · External reference
10.1016/j.csbj.2021.03.001 · Admitted local publication
10.1126/science.aax4438
10.1126/science.aax4438 · External reference
10.1038/ng.3477
10.1038/ng.3477 · External reference
10.1038/nbt.4235
10.1038/nbt.4235 · External reference
10.1038/s41571-018-0002-6
10.1038/s41571-018-0002-6 · External reference
Unresolved reference
2020 · External reference
10.1016/j.cell.2018.03.035
10.1016/j.cell.2018.03.035 · External reference
10.1089/omi.2013.0017
10.1089/omi.2013.0017 · External reference
Applications of support vector machine (svm) learning in cancer genomics
2018 · External reference
Deep learning-based multi-omics integration robustly predicts survival in liver cancer
10.1158/1078-0432.ccr-17-0853 · 2018 · External reference
10.1016/j.gpb.2019.02.003
10.1016/j.gpb.2019.02.003 · External reference
Integrating multi-omics data through deep learning for accurate cancer prognosis prediction
10.1016/j.compbiomed.2021.104481 · 2021 · External reference
Deep learning in breast cancer risk assessment: evaluation of convolutional neural networks on a clinical dataset of full-field digital mammograms
2017 · External reference
10.1109/waina.2009.165
10.1109/waina.2009.165 · 2009 · External reference
10.1001/jama.2017.14585
10.1001/jama.2017.14585 · External reference
Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists
10.1093/annonc/mdy166 · 2018 · External reference
10.1093/bioinformatics/btp630
10.1093/bioinformatics/btp630 · External reference
Identifying cancer biomarkers by network-constrained support vector machines
10.1186/1752-0509-5-161 · 2011 · External reference
Deepgene: an advanced cancer type classifier based on deep learning and somatic point mutations
10.1186/s12859-016-1334-9 · 2016 · External reference
Mvp: predicting pathogenicity of missense variants by deep learning
2018 · External reference
10.1016/j.cell.2018.03.034
10.1016/j.cell.2018.03.034 · External reference
Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models
10.1038/s41598-017-11817-6 · 2017 · External reference
A machine learning classifier trained on cancer transcriptomes detects nf1 inactivation signal in glioblastoma
10.1186/s12864-017-3519-7 · 2017 · External reference
Discoversl: an r package for multi-omic data driven prediction of synthetic lethality in cancers
2019 · External reference
Exp2sl: A machine learning framework for cell-line-specific synthetic lethality prediction
10.3389/fphar.2020.00112 · 2020 · External reference
10.1093/nar/gkz1023
10.1093/nar/gkz1023 · External reference
Deep learning in pharmacogenomics: from gene regulation to patient stratification
2018 · External reference
10.1016/j.drudis.2018.01.039
10.1016/j.drudis.2018.01.039 · External reference
Prioritization of anticancer drugs against a cancer using genomic features of cancer cells: A step towards personalized medicine
10.1038/srep23857 · 2016 · External reference
Improving drug sensitivity prediction using different types of data
2015 · External reference
10.1093/bioinformatics/bty294
10.1093/bioinformatics/bty294 · External reference
10.1007/s00439-019-01970-5
10.1007/s00439-019-01970-5 · External reference
10.2217/epi-2016-0005
10.2217/epi-2016-0005 · External reference
10.1080/15592294.2017.1329068
10.1080/15592294.2017.1329068 · External reference
10.1111/nan.12598
10.1111/nan.12598 · External reference
Predicting genome architecture: Challenges and solutions
10.3389/fgene.2020.617202 · 2020 · External reference
Predicting DNA methylation state of CpG dinucleotide using genome topological features and deep networks
2016 · External reference
10.1093/bioinformatics/btx243
10.1093/bioinformatics/btx243 · External reference
10.1093/nar/gkz156
10.1093/nar/gkz156 · External reference
Deep learning-based enhancement of epigenomics data with atacworks
10.1038/s41467-021-21765-5 · 2021 · External reference
10.1038/nrg3454
10.1038/nrg3454 · External reference
Unresolved reference
2019 · External reference
10.1038/nmeth.1906
10.1038/nmeth.1906 · External reference
Chrom3d: three-dimensional genome modeling from hi-c and nuclear lamin-genome contacts
10.1186/s13059-016-1146-2 · 2017 · External reference
10.1109/tcbb.2018.2791439
10.1109/tcbb.2018.2791439 · External reference
10.1109/tcbb.2018.2838669
10.1109/tcbb.2018.2838669 · External reference
10.1371/journal.pcbi.1005665
10.1371/journal.pcbi.1005665 · External reference
10.1038/s41592-020-0958-x
10.1038/s41592-020-0958-x · External reference
10.1038/s41592-020-0960-3
10.1038/s41592-020-0960-3 · External reference
10.1016/s0092-8674(00)81845-0
10.1016/s0092-8674(00)81845-0 · External reference
10.1126/science.270.5235.484
10.1126/science.270.5235.484 · External reference
10.1016/j.cell.2011.03.014
10.1016/j.cell.2011.03.014 · External reference
10.1038/s41576-019-0158-7
10.1038/s41576-019-0158-7 · External reference
10.1038/s41576-018-0073-3
10.1038/s41576-018-0073-3 · External reference
10.1038/nature11233
10.1038/nature11233 · External reference
An integrated encyclopedia of DNA elements in the human genome
2012 · External reference
Binding of cells to matrixes of distinct antibodies coated on solid surface
10.1016/0022-1759(83)90318-6 · 1983 · External reference
10.1126/science.270.5235.467
10.1126/science.270.5235.467 · External reference
Unresolved reference
2008 · External reference
Unresolved reference
2014 · External reference
RNA-Seq: a revolutionary tool for transcriptomics
10.1038/nrg2484 · 2010 · External reference
Unresolved reference
2019 · External reference
10.1371/journal.pcbi.1005457
10.1371/journal.pcbi.1005457 · External reference
10.1093/nar/gky955
10.1093/nar/gky955 · External reference
Assessment of protein coding measures
10.1093/nar/20.24.6441 · 1992 · External reference
Discrimination of Non-Protein-Coding Transcripts from Protein-Coding mRNA
10.4161/rna.3.1.2789 · 2006 · External reference
Coding potential of the products of alternative splicing in human
10.1186/gb-2011-12-1-r9 · 2011 · External reference
Distinguishing protein-coding from non-coding RNAs through support vector machines
2006 · External reference
CPC: Assess the protein-coding potential of transcripts using sequence features and support vector machine
2007 · External reference
PLEK: A tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme
10.1186/1471-2105-15-311 · 2014 · External reference
10.1186/s12864-017-4178-4
10.1186/s12864-017-4178-4 · External reference
10.1371/journal.pone.0154567
10.1371/journal.pone.0154567 · External reference
CPAT: Coding-potential assessment tool using an alignment-free logistic regression model
2013 · External reference
CPC2: A fast and accurate coding potential calculator based on sequence intrinsic features
2017 · External reference
LncRNAnet: Long non-coding RNA identification using deep learning
2018 · External reference
A deep recurrent neural network discovers complex biological rules to decipher RNA protein-coding potential
10.1093/nar/gky567 · 2018 · External reference
Unresolved reference
2019 · External reference
RNAsamba: neural network-based assessment of the protein-coding potential of RNA sequences
10.1093/nargab/lqz024 · 2020 · External reference
Archetypal transcriptional blocks underpin yeast gene regulation in response to changes in growth conditions
10.1038/s41598-018-26170-5 · 2018 · External reference
Applications of machine learning to diagnosis and treatment of neurodegenerative diseases
10.1038/s41582-020-0377-8 · 2020 · External reference
10.1371/journal.pcbi.1006826
10.1371/journal.pcbi.1006826 · External reference
10.1101/857169
10.1101/857169 · External reference
Visualizing data using t-SNE
2008 · External reference
Unresolved reference
External reference
10.1016/j.celrep.2021.109442
10.1016/j.celrep.2021.109442 · External reference
An accurate and robust imputation method scimpute for single-cell rna-seq data
2018 · External reference
Drimpute: imputing dropout events in single cell rna sequencing data
10.1186/s12859-018-2226-y · 2018 · External reference
Deepimpute: an accurate, fast and scalable deep neural network method to impute single-cell rna-seq data
2018 · External reference
10.1038/418236a
10.1038/418236a · External reference
10.1038/nature07509
10.1038/nature07509 · External reference
10.1093/nar/gkq197
10.1093/nar/gkq197 · External reference
10.1038/nbt964
10.1038/nbt964 · External reference
10.1016/j.ccell.2018.07.001
10.1016/j.ccell.2018.07.001 · External reference
Isoform-resolved correlation analysis between mRNA abundance regulation and protein level degradation
10.15252/msb.20199170 · 2020 · External reference
COSSMO: Predicting competitive alternative splice site selection using deep learning
10.1101/255257 · 2018 · External reference
Integrative deep models for alternative splicing
10.1101/104869 · 2017 · External reference
MATS: A Bayesian framework for flexible detection of differential alternative splicing from RNA-Seq data
2012 · External reference
Deep-learning augmented RNA-seq analysis of transcript splicing
2019 · External reference
Deep learning of the tissue-regulated splicing code
2014 · External reference
10.1016/j.cell.2018.12.015
10.1016/j.cell.2018.12.015 · External reference
DNAFSMiner: a web-based software toolbox to recognize two types of functional sites in DNA sequences
10.1093/bioinformatics/bth437 · 2005 · External reference
Dragon polya spotter: predictor of poly(a) motifs within human genomic dna sequences
10.1093/bioinformatics/btt161 · 2013 · External reference
Recognition of 3’-processing sites of human mrna precursors
1997 · External reference
Detection of polyadenylation signals in human dna sequences
10.1016/s0378-1119(99)00104-3 · 1999 · External reference
10.1093/bioinformatics/btl394
10.1093/bioinformatics/btl394 · External reference
MicroRNA-27b regulates the expression of matrix metalloproteinase 13 in human osteoarthritis chondrocytes
10.1002/art.27329 · 2010 · External reference
Grid-based prediction of torsion angle probabilities of protein backbone and its application to discrimination of protein intrinsic disorder regions and selection of model structures
10.1186/s12859-018-2031-7 · 2018 · External reference
Deerect-polya: a robust and generic deep learning method for pas identification
10.1093/bioinformatics/bty991 · 2019 · External reference
Inference of the human polyadenylation code
10.1093/bioinformatics/bty211 · 2017 · External reference
10.1128/jvi.65.10.5165-5173.1991
10.1128/jvi.65.10.5165-5173.1991 · External reference
Effect of RNA secondary structure on polyadenylation site selection
10.1101/gad.5.7.1277 · 1991 · External reference
Secondary structure as a functional feature in the downstream region of mammalian polyadenylation signals
10.1128/mcb.24.7.2789-2796.2004 · 2004 · External reference
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