Exosomes, new biomarkers in early cancer detection
Exosomes are endosomal-derived vesicles, playing a major role in cell-to-cell
communication. Multiple cells secret these vesicles to induce and inhibit different cellular …
communication. Multiple cells secret these vesicles to induce and inhibit different cellular …
Machine learning and artificial neural network accelerated computational discoveries in materials science
Artificial intelligence (AI) has been referred to as the “fourth paradigm of science,” and as
part of a coherent toolbox of data‐driven approaches, machine learning (ML) dramatically …
part of a coherent toolbox of data‐driven approaches, machine learning (ML) dramatically …
A machine-learning-based prediction method for hypertension outcomes based on medical data
W Chang, Y Liu, Y Xiao, X Yuan, X Xu, S Zhang… - Diagnostics, 2019 - mdpi.com
The outcomes of hypertension refer to the death or serious complications (such as
myocardial infarction or stroke) that may occur in patients with hypertension. The outcomes …
myocardial infarction or stroke) that may occur in patients with hypertension. The outcomes …
iEnhancer-5Step: identifying enhancers using hidden information of DNA sequences via Chou's 5-step rule and word embedding
An enhancer is a short (50–1500bp) region of DNA that plays an important role in gene
expression and the production of RNA and proteins. Genetic variation in enhancers has …
expression and the production of RNA and proteins. Genetic variation in enhancers has …
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 …
ACP-DL: a deep learning long short-term memory model to predict anticancer peptides using high-efficiency feature representation
Cancer is a well-known killer of human beings, which has led to countless deaths and
misery. Anticancer peptides open a promising perspective for cancer treatment, and they …
misery. Anticancer peptides open a promising perspective for cancer treatment, and they …
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 …
Identification of clathrin proteins by incorporating hyperparameter optimization in deep learning and PSSM profiles
Abstract Background and Objectives Clathrin is an adaptor protein that serves as the
principal element of the vesicle-coating complex and is important for the membrane …
principal element of the vesicle-coating complex and is important for the membrane …
FAD-BERT: improved prediction of FAD binding sites using pre-training of deep bidirectional transformers
The electron transport chain is a series of protein complexes embedded in the process of
cellular respiration, which is an important process to transfer electrons and other …
cellular respiration, which is an important process to transfer electrons and other …