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Structure-Activity Relationship

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Artificial intelligence and big data facilitated targeted drug discovery.

Stroke and vascular neurology
Different kinds of biological databases publicly available nowadays provide us a goldmine of multidiscipline big data. The Cancer Genome Atlas is a cancer database including detailed information of many patients with cancer. DrugBank is a database in...

Function2Form Bridge-Toward synthetic protein holistic performance prediction.

Proteins
Protein engineering and synthetic biology stand to benefit immensely from recent advances in silico tools for structural and functional analyses of proteins. In the context of designing novel proteins, current in silico tools inform the user on indiv...

Improvement of Epitope Prediction Using Peptide Sequence Descriptors and Machine Learning.

International journal of molecular sciences
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 ...

Evaluation of different virtual screening strategies on the basis of compound sets with characteristic core distributions and dissimilarity relationships.

Journal of computer-aided molecular design
In this work, computational compound screening strategies on the basis of two- and three-dimensional (2D and 3D) molecular representations were investigated including similarity searching and support vector machine (SVM) ranking. Calculations based o...

Evaluating Polymer Representations via Quantifying Structure-Property Relationships.

Journal of chemical information and modeling
Machine learning techniques are being applied in quantifying structure-property relationships for a wide variety of materials, where the properly represented materials play key roles. Although algorithms for representation learning are extensively st...

Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance.

Journal of chemical information and modeling
Drug-induced liver injury (DILI), one of the most common adverse effects, leads to drug development failure or withdrawal from the market in most cases, showing an emerging challenge that is to accurately predict DILI in the early stage. Recently, th...

Analysis of the Deleterious Single Nucleotide Polymorphisms Impact on Estrogen Receptor Alpha-p53 Interaction: A Machine Learning Approach.

International journal of molecular sciences
Breast cancer is a leading cancer type and one of the major health issues faced by women around the world. Some of its major risk factors include body mass index, hormone replacement therapy, family history and germline mutations. Of these risk facto...

Deep Learning to Speed up the Development of Structure-Property Relations For Hexagonal Boron Nitride and Graphene.

Small (Weinheim an der Bergstrasse, Germany)
Structure-property maps play a key role in accelerated materials discovery. The current norm for developing these maps includes computationally expensive physics-based simulations. Here, the capabilities of deep learning agents are explored such as c...

In Need of Bias Control: Evaluating Chemical Data for Machine Learning in Structure-Based Virtual Screening.

Journal of chemical information and modeling
Reports of successful applications of machine learning (ML) methods in structure-based virtual screening (SBVS) are increasing. ML methods such as convolutional neural networks show promising results and often outperform traditional methods such as e...