![A Review on the Recent Developments of Sequence-based Protein Feature Extraction Methods | Bentham Science A Review on the Recent Developments of Sequence-based Protein Feature Extraction Methods | Bentham Science](https://www.eurekaselect.com/images/graphical-abstract/cbio/14/3/002.jpg)
A Review on the Recent Developments of Sequence-based Protein Feature Extraction Methods | Bentham Science
![Predicting transcription factor binding sites using DNA shape features based on shared hybrid deep learning architecture: Molecular Therapy - Nucleic Acids Predicting transcription factor binding sites using DNA shape features based on shared hybrid deep learning architecture: Molecular Therapy - Nucleic Acids](https://www.cell.com/cms/attachment/65392d5e-09f3-4188-b2c3-f8c424fc895b/fx1_lrg.jpg)
Predicting transcription factor binding sites using DNA shape features based on shared hybrid deep learning architecture: Molecular Therapy - Nucleic Acids
![Life | Free Full-Text | Identifying Intrinsically Disordered Protein Regions through a Deep Neural Network with Three Novel Sequence Features Life | Free Full-Text | Identifying Intrinsically Disordered Protein Regions through a Deep Neural Network with Three Novel Sequence Features](https://www.mdpi.com/life/life-12-00345/article_deploy/html/images/life-12-00345-g001.png)
Life | Free Full-Text | Identifying Intrinsically Disordered Protein Regions through a Deep Neural Network with Three Novel Sequence Features
![Structure-based protein function prediction using graph convolutional networks | Nature Communications Structure-based protein function prediction using graph convolutional networks | Nature Communications](https://media.springernature.com/m685/springer-static/image/art%3A10.1038%2Fs41467-021-23303-9/MediaObjects/41467_2021_23303_Fig1_HTML.png)
Structure-based protein function prediction using graph convolutional networks | Nature Communications
![Repertoire analyses reveal T cell antigen receptor sequence features that influence T cell fate | Nature Immunology Repertoire analyses reveal T cell antigen receptor sequence features that influence T cell fate | Nature Immunology](https://media.springernature.com/m685/springer-static/image/art%3A10.1038%2Fs41590-022-01129-x/MediaObjects/41590_2022_1129_Fig1_HTML.png)
Repertoire analyses reveal T cell antigen receptor sequence features that influence T cell fate | Nature Immunology
Sequence features, multiple sequence alignments and neighbor-joining... | Download Scientific Diagram
Steps for classification of DNA sequence: feature extraction, feature... | Download Scientific Diagram
Design of the sequence+shape feature vector, and TF family-specific... | Download Scientific Diagram
Sequence features of viral and human Internal Ribosome Entry Sites predictive of their activity | PLOS Computational Biology
![An Evaluation of Machine Learning Approaches for the Prediction of Essential Genes in Eukaryotes Using Protein Sequence-Derived Features - ScienceDirect An Evaluation of Machine Learning Approaches for the Prediction of Essential Genes in Eukaryotes Using Protein Sequence-Derived Features - ScienceDirect](https://ars.els-cdn.com/content/image/1-s2.0-S2001037019301357-gr1.jpg)
An Evaluation of Machine Learning Approaches for the Prediction of Essential Genes in Eukaryotes Using Protein Sequence-Derived Features - ScienceDirect
![Feature Extraction Approaches for Biological Sequences: A Comparative Study of Mathematical Models | bioRxiv Feature Extraction Approaches for Biological Sequences: A Comparative Study of Mathematical Models | bioRxiv](https://www.biorxiv.org/content/biorxiv/early/2020/06/09/2020.06.08.140368/F6.large.jpg)
Feature Extraction Approaches for Biological Sequences: A Comparative Study of Mathematical Models | bioRxiv
![Prediction of DNA binding proteins using local features and long-term dependencies with primary sequences based on deep learning [PeerJ] Prediction of DNA binding proteins using local features and long-term dependencies with primary sequences based on deep learning [PeerJ]](https://dfzljdn9uc3pi.cloudfront.net/2021/11262/1/fig-1-2x.jpg)
Prediction of DNA binding proteins using local features and long-term dependencies with primary sequences based on deep learning [PeerJ]
![Deciphering how naturally occurring sequence features impact the phase behaviours of disordered prion-like domains | Nature Chemistry Deciphering how naturally occurring sequence features impact the phase behaviours of disordered prion-like domains | Nature Chemistry](https://media.springernature.com/m685/springer-static/image/art%3A10.1038%2Fs41557-021-00840-w/MediaObjects/41557_2021_840_Figa_HTML.png)
Deciphering how naturally occurring sequence features impact the phase behaviours of disordered prion-like domains | Nature Chemistry
![Feature extraction. (A) Sequence features consist of two parts. The... | Download Scientific Diagram Feature extraction. (A) Sequence features consist of two parts. The... | Download Scientific Diagram](https://www.researchgate.net/publication/326814782/figure/fig1/AS:655599398318081@1533318485976/Feature-extraction-A-Sequence-features-consist-of-two-parts-The-first-part-is-the.png)
Feature extraction. (A) Sequence features consist of two parts. The... | Download Scientific Diagram
![Model Overview: (a) represents the generation of feature sequence from... | Download Scientific Diagram Model Overview: (a) represents the generation of feature sequence from... | Download Scientific Diagram](https://www.researchgate.net/publication/326570264/figure/fig1/AS:651764500021248@1532404174701/Model-Overview-a-represents-the-generation-of-feature-sequence-from-convolutional.png)