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Table 3 Genomic tools/algorithm based on deep learning architecture for gene expression regulation

From: A review of deep learning applications in human genomics using next-generation sequencing data

Tools

DL model

Application

Input/Output

Website Code Source

References

DanQ

CNN + BLSTM

To predict DNA function directly from sequence data

.mat /.mat

https://github.com/uci-cbcl/DanQ

[152]

SPEID

CNN + LSTM

For enhancer–promoter interaction (EPI) prediction

.mat /.mat

https://github.com/ma-compbio/SPEID

[153]

EP2vec

NLP + GBRT

To predict enhancer–promoter interactions (EPIs)

CSV / CSV

https://github.com/wanwenzeng/ep2vec

[154]

D-GEX (deep learning for gene expression)

FNN

To understand the expression of target genes from the expression of landmark genes

.cel, txt, BAM / txt

https://github.com/uci-cbcl/D-GEX

[155]

DeepExpression

CNN

To predict gene expression using promoter sequences and enhancer–promoter interactions

.txt /.txt

https://github.com/wanwenzeng/DeepExpression

[156]

DeepGSR

CNN + ANN

To recognise various types of genomic signals and regions (GSRs) in genomic DNA (e.g. splice sites and stop codon)

FASTA /.txt

https://zenodo.org/record/1117159#.Xp4B4y2B1p8

[157]

SpliceAI

CNN

To identify splice function from pre-mRNA sequencing

VCF / VCF

https://github.com/Illumina/SpliceAI

[71]

SpliceRover

CNN

For splice site prediction

FASTA /.txt

N/A

[158]

Splice2Deep

CNN

For splice site prediction in Genomic DNA

FASTA /.txt

https://github.com/SomayahAlbaradei/Splice_Deep

[29]

DeepBind

CNN

To characterise DNA- and RNA-binding protein specificity

FASTA /.txt

https://github.com/MedChaabane/DeepBind-with-PyTorch

[111]

Gene2vec

NLP

To produce a representation of genes distribution and predict gene–gene interaction

.txt /.txt

https://github.com/jingcheng-du/Gene2vec

[130]

MPRA-DragoNN

CNN

To predict and analyse the regulatory DNA sequences and non-coding genetic variants

N/A

https://github.com/kundajelab/MPRA-DragoNN

[77]

BiRen

CNN + GRU + RNN

For enhancers predictions

BED, BigWig /CSV

https://github.com/wenjiegroup/BiRen

[159]

APARENT (APA REgression NeT)

CNN

To predict and engineer the human 3' UTR Alternative Polyadenylation (APA) and annotate pathogenetic variants

FASTA / CSV

https://github.com/johli/aparent

[72]

LaBranchoR (LSTM Branchpoint Retriever)

BLSTM

To predict the location of RNA splicing branchpoint

FASTA / FASTA

https://github.com/jpaggi/labranchor

[160]

COSSMO

CNN, BLSTM + ResNet

To predict the splice site sequencing and splice factors

TSV, CSV /CSV

http://cossmo.genes.toronto.edu/

[79]

Xpresso

CNN

To predict gene expression levels from genomic sequence

FASTA /.txt

https://github.com/vagarwal87/Xpresso

[73]

DeepLoc

CNN + BLSTM

To predict subcellular localisation of protein from sequencing data

FASTA/ prediction score

https://github.com/JJAlmagro/subcellular_localization

[161]

SPOT-RNA

CNN

To predict RNA Secondary Structure

FASTA /.bpseq,.ct, and.prob

https://github.com/jaswindersingh2/SPOT-RNA/

[162]

DeepCLIP

CNN + BLSTM

For predicting the effect of mutations on protein–RNA binding

FASTA /.txt

https://github.com/deepclip/deepclip

[163]

DECRES (DEep learning for identifying Cis-Regulatory ElementS)

MLP + CNN

To predict active enhancers and promoters across the human genome

FASTA /.txt

https://github.com/yifeng-li/DECRES

[74]

DeepChrome

CNN

For prediction of gene expression levels from histone modification data

Bam / TSV

https://github.com/QData/DeepChrome

[164]

DARTS

DNN + BHT

Deep learning augmented RNA-seq analysis of transcript splicing

.txt

https://github.com/Xinglab/DARTS

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