| AI | Artificial intelligence |
| ANN | Artificial neural network |
| ATAC-seq | Assay for transposase-accessible chromatin using sequencing |
| AUC | Area under the curve |
| CITE-seq | Cellular indexing of transcriptomes and epitopes by sequencing |
| CNN | Convolutional neural network |
| CNV | Copy number variation |
| CRF | Conditional random field |
| CTC | Connectionist temporal classification |
| ctDNA | Circulating tumor DNA |
| DL | Deep learning |
| DEA | Differential expression analysis |
| DMR | Differentially methylated region |
| EMBL-EBI | European Bioinformatics Institute |
| GATK | Genome Analysis Toolkit |
| GBM | Gradient boosting machine |
| GEO | Gene Expression Omnibus |
| GNN | Graph neural network |
| GRN | Gene regulatory network |
| HDP | Hierarchical Dirichlet process |
| HGP | Human Genome Project |
| HMM | Hidden Markov model |
| IGCN | Integrative graph convolutional network |
| IPD | Interpulse duration |
| LSTM | Long short-term memory |
| ML | Machine learning |
| m5C | 5-methylcytosine |
| m6A | N6-methyladenosine |
| hm5C | 5-hydroxymethylcytosine |
| ML | Machine learning |
| mRNA | Messenger RNA |
| NGS | Next-generation sequencing |
| ONT | Oxford Nanopore Technologies |
| PCA | Principal component analysis |
| PCR | Polymerase chain reaction |
| RF | Random forest |
| RNN | Recurrent neural network |
| scRNA-seq | Single-cell RNA sequencing |
| SdAs | Stacked denoising autoencoders |
| SNP | Single nucleotide polymorphism |
| SVM | Support vector machine |
| TCGA | The Cancer Genome Atlas |
| TGS | Third-generation sequencing |
| t-SNE | t-distributed stochastic neighbor embedding |
| UMAP | Uniform manifold approximation and projection |
| VAE | Variational autoencoder |
| WGBS | Whole-genome bisulfite sequencing |