AIMC Journal:
International journal of molecular sciences
Showing 361 to 370 of 423 articles
DeepMiR2GO: Inferring Functions of Human MicroRNAs Using a Deep Multi-Label Classification Model.
International journal of molecular sciences
Nov 30, 2019
MicroRNAs (miRNAs) are a highly abundant collection of functional non-coding RNAs involved in cellular regulation and various complex human diseases. Although a large number of miRNAs have been identified, most of their physiological functions remain...
Approach for the Definition of radiomiRNomic Signatures for Breast Cancer Differential Diagnosis.
International journal of molecular sciences
Nov 20, 2019
UNLABELLED: Personalized medicine relies on the integration and consideration of specific characteristics of the patient, such as tumor phenotypic and genotypic profiling.
Novel Descriptors and Digital Signal Processing- Based Method for Protein Sequence Activity Relationship Study.
International journal of molecular sciences
Nov 11, 2019
The work aiming to unravel the correlation between protein sequence and function in the absence of structural information can be highly rewarding. We present a new way of considering descriptors from the amino acids index database for modeling and pr...
Prediction Model with High-Performance Constitutive Androstane Receptor (CAR) Using DeepSnap-Deep Learning Approach from the Tox21 10K Compound Library.
International journal of molecular sciences
Sep 30, 2019
The constitutive androstane receptor (CAR) plays pivotal roles in drug-induced liver injury through the transcriptional regulation of drug-metabolizing enzymes and transporters. Thus, identifying regulatory factors for CAR activation is important for...
Skin Doctor: Machine Learning Models for Skin Sensitization Prediction that Provide Estimates and Indicators of Prediction Reliability.
International journal of molecular sciences
Sep 28, 2019
The ability to predict the skin sensitization potential of small organic molecules is of high importance to the development and safe application of cosmetics, drugs and pesticides. One of the most widely accepted methods for predicting this hazard is...
LDAPred: A Method Based on Information Flow Propagation and a Convolutional Neural Network for the Prediction of Disease-Associated lncRNAs.
International journal of molecular sciences
Sep 10, 2019
Long non-coding RNAs (lncRNAs) play a crucial role in the pathogenesis and development of complex diseases. Predicting potential lncRNA-disease associations can improve our understanding of the molecular mechanisms of human diseases and help identify...
Improvement of Epitope Prediction Using Peptide Sequence Descriptors and Machine Learning.
International journal of molecular sciences
Sep 5, 2019
In this work, we improved a previous model used for the prediction of proteomes as new B-cell epitopes in vaccine design. The predicted epitope activity of a queried peptide is based on its sequence, a known reference epitope sequence under specific ...
CNNDLP: A Method Based on Convolutional Autoencoder and Convolutional Neural Network with Adjacent Edge Attention for Predicting lncRNA-Disease Associations.
International journal of molecular sciences
Aug 30, 2019
It is well known that the unusual expression of long non-coding RNAs (lncRNAs) is closely related to the physiological and pathological processes of diseases. Therefore, inferring the potential lncRNA-disease associations are helpful for understandin...
Machine Learning to Understand the Immune-Inflammatory Pathways in Fibromyalgia.
International journal of molecular sciences
Aug 29, 2019
Fibromyalgia (FM) is a chronic syndrome characterized by widespread musculoskeletal pain, and physical and emotional symptoms. Although its pathophysiology is largely unknown, immune-inflammatory pathways may be involved. We examined serum interleuki...
Artificial Neural Network Approach for Modelling of Mercury Ions Removal from Water Using Functionalized CNTs with Deep Eutectic Solvent.
International journal of molecular sciences
Aug 28, 2019
Multi-walled carbon nanotubes (CNTs) functionalized with a deep eutectic solvent (DES) were utilized to remove mercury ions from water. An artificial neural network (ANN) technique was used for modelling the functionalized CNTs adsorption capacity. T...
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