AIMC Journal:
International journal of molecular sciences

Showing 341 to 350 of 423 articles

Prediction Power on Cardiovascular Disease of Neuroimmune Guidance Cues Expression by Peripheral Blood Monocytes Determined by Machine-Learning Methods.

International journal of molecular sciences Sep 2, 2020
Atherosclerosis is the underlying pathology in a major part of cardiovascular disease, the leading cause of mortality in developed countries. The infiltration of monocytes into the vessel walls of large arteries is a key denominator of atherogenesis,...
Cardiovascular Diseases Middle Aged Transcriptome Female Adult Male Humans Ephrins Machine Learning Netrin-1 Biomarkers Semaphorins Case-Control Studies Cohort Studies Monocytes
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Deep Learning Modeling of Androgen Receptor Responses to Prostate Cancer Therapies.

International journal of molecular sciences Aug 14, 2020
Gain-of-function mutations in human androgen receptor (AR) are among the major causes of drug resistance in prostate cancer (PCa). Identifying mutations that cause resistant phenotype is of critical importance for guiding treatment protocols, as well...
Male Deep Learning Cell Line, Tumor Humans Neural Networks, Computer Receptors, Androgen Transcription, Genetic Androgen Receptor Antagonists ROC Curve Prostatic Neoplasms Mutation
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DeepPred-SubMito: A Novel Submitochondrial Localization Predictor Based on Multi-Channel Convolutional Neural Network and Dataset Balancing Treatment.

International journal of molecular sciences Aug 9, 2020
Mitochondrial proteins are physiologically active in different compartments, and their abnormal location will trigger the pathogenesis of human mitochondrial pathologies. Correctly identifying submitochondrial locations can provide information for di...
Protein Transport Mitochondrial Proteins Deep Learning Mitochondrial Membranes Humans Neural Networks, Computer Computational Biology Algorithms Mitochondria
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Predicting In Vitro Neurotoxicity Induced by Nanoparticles Using Machine Learning.

International journal of molecular sciences Jul 25, 2020
The practice of non-testing approaches in nanoparticles hazard assessment is necessary to identify and classify potential risks in a cost effective and timely manner. Machine learning techniques have been applied in the field of nanotoxicology with e...
Models, Neurological Predictive Value of Tests Neurotoxins Humans Machine Learning Nanoparticles
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lncRNA_Mdeep: An Alignment-Free Predictor for Distinguishing Long Non-Coding RNAs from Protein-Coding Transcripts by Multimodal Deep Learning.

International journal of molecular sciences Jul 23, 2020
Long non-coding RNAs (lncRNAs) play crucial roles in diverse biological processes and human complex diseases. Distinguishing lncRNAs from protein-coding transcripts is a fundamental step for analyzing the lncRNA functional mechanism. However, the exp...
Databases, Nucleic Acid Deep Learning Humans Mice RNA, Long Noncoding Software Animals
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Protein-Protein Interactions Efficiently Modeled by Residue Cluster Classes.

International journal of molecular sciences Jul 6, 2020
Predicting protein-protein interactions (PPI) represents an important challenge in structural bioinformatics. Current computational methods display different degrees of accuracy when predicting these interactions. Different factors were proposed to h...
Sequence Analysis, Protein Algorithms Artificial Intelligence Machine Learning Proteins Databases, Protein Protein Interaction Mapping Computational Biology Cluster Analysis
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Similarity-Based Methods and Machine Learning Approaches for Target Prediction in Early Drug Discovery: Performance and Scope.

International journal of molecular sciences May 19, 2020
Computational methods for predicting the macromolecular targets of drugs and drug-like compounds have evolved as a key technology in drug discovery. However, the established validation protocols leave several key questions regarding the performance a...
Drug Discovery Knowledge Bases Molecular Targeted Therapy Machine Learning Reproducibility of Results
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In Silico Prediction of Intestinal Permeability by Hierarchical Support Vector Regression.

International journal of molecular sciences May 19, 2020
The vast majority of marketed drugs are orally administrated. As such, drug absorption is one of the important drug metabolism and pharmacokinetics parameters that should be assessed in the process of drug discovery and development. A nonlinear quant...
Humans Computer Simulation Reproducibility of Results Animals Intestines Rats Support Vector Machine Regression Analysis Permeability
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Convolutional Neural Network Can Recognize Drug Resistance of Single Cancer Cells.

International journal of molecular sciences Apr 30, 2020
It is known that single or isolated tumor cells enter cancer patients' circulatory systems. These circulating tumor cells (CTCs) are thought to be an effective tool for diagnosing cancer malignancy. However, handling CTC samples and evaluating CTC se...
Neoplasms Machine Learning Antineoplastic Agents Humans Cells, Cultured Deep Learning Neural Networks, Computer Cell Line, Tumor Precision Medicine Single-Cell Analysis Drug Resistance, Neoplasm
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Combination Strategies for Immune-Checkpoint Blockade and Response Prediction by Artificial Intelligence.

International journal of molecular sciences Apr 19, 2020
The therapeutic concept of unleashing a pre-existing immune response against the tumor by the application of immune-checkpoint inhibitors (ICI) has resulted in long-term survival in advanced cancer patient subgroups. However, the majority of patients...
T-Lymphocyte Subsets Animals Neoplasms Immune Checkpoint Inhibitors Humans Immunotherapy Antineoplastic Agents, Immunological Artificial Intelligence Cancer Vaccines Biomarkers, Tumor Combined Modality Therapy Treatment Outcome Molecular Targeted Therapy
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