A transformer architecture based on BERT and 2D convolutional neural network to identify DNA enhancers from sequence information
Recently, language representation models have drawn a lot of attention in the natural
language processing field due to their remarkable results. Among them, bidirectional …
language processing field due to their remarkable results. Among them, bidirectional …
Exploring deep learning for complex trait genomic prediction in polyploid outcrossing species
Genomic prediction (GP) is the procedure whereby the genetic merits of untested candidates
are predicted using genome wide marker information. Although numerous examples of GP …
are predicted using genome wide marker information. Although numerous examples of GP …
Classifying promoters by interpreting the hidden information of DNA sequences via deep learning and combination of continuous fasttext N-grams
A promoter is a short region of DNA (100–1,000 bp) where transcription of a gene by RNA
polymerase begins. It is typically located directly upstream or at the 5′ end of the …
polymerase begins. It is typically located directly upstream or at the 5′ end of the …
DBP-CNN: Deep learning-based prediction of DNA-binding proteins by coupling discrete cosine transform with two-dimensional convolutional neural network
To improve the prediction of DNA-binding Proteins (DBPs), this paper presents a deep
learning-based method, named DBP-CNN. To efficiently extract the important features, we …
learning-based method, named DBP-CNN. To efficiently extract the important features, we …
An Efficient hybrid filter-wrapper metaheuristic-based gene selection method for high dimensional datasets
J Pirgazi, M Alimoradi, T Esmaeili Abharian… - Scientific reports, 2019 - nature.com
Feature selection problem is one of the most significant issues in data classification. The
purpose of feature selection is selection of the least number of features in order to increase …
purpose of feature selection is selection of the least number of features in order to increase …
A sequence-based prediction of Kruppel-like factors proteins using XGBoost and optimized features
Krüppel-like factors (KLF) refer to a group of conserved zinc finger-containing transcription
factors that are involved in various physiological and biological processes, including cell …
factors that are involved in various physiological and biological processes, including cell …
An automated ECG beat classification system using deep neural networks with an unsupervised feature extraction technique
An automated classification system based on a Deep Learning (DL) technique for Cardiac
Disease (CD) monitoring and detection is proposed in this paper. The proposed DL …
Disease (CD) monitoring and detection is proposed in this paper. The proposed DL …
A new method for CTC images recognition based on machine learning
B He, Q Lu, J Lang, H Yu, C Peng, P Bing… - … in Bioengineering and …, 2020 - frontiersin.org
Circulating tumor cells (CTCs) derived from primary tumors and/or metastatic tumors are
markers for tumor prognosis, and can also be used to monitor therapeutic efficacy and tumor …
markers for tumor prognosis, and can also be used to monitor therapeutic efficacy and tumor …
A computational framework based on ensemble deep neural networks for essential genes identification
Essential genes contain key information of genomes that could be the key to a
comprehensive understanding of life and evolution. Because of their importance, studies of …
comprehensive understanding of life and evolution. Because of their importance, studies of …
DBP-DeepCNN: prediction of DNA-binding proteins using wavelet-based denoising and deep learning
DNA-binding proteins (DBPs) are highly concerned with several types of cancers (lung,
breast, and liver), other fatal diseases (AIDS/HIV, asthma), and are used in the designing of …
breast, and liver), other fatal diseases (AIDS/HIV, asthma), and are used in the designing of …