AIMC Topic: Software

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The Application of Deep Learning for the Evaluation of User Interfaces.

Sensors (Basel, Switzerland)
In this study, we tested the ability of a machine-learning model (ML) to evaluate different user interface designs within the defined boundaries of some given software. Our approach used ML to automatically evaluate existing and new web application d...

DeepCV: A Deep Learning Framework for Blind Search of Collective Variables in Expanded Configurational Space.

Journal of chemical information and modeling
We present (DeepCV), a computer code that provides an efficient and customizable implementation of the deep autoencoder neural network (DAENN) algorithm that has been developed in our group for computing collective variables (CVs) and can be used wi...

microbeSEG: A deep learning software tool with OMERO data management for efficient and accurate cell segmentation.

PloS one
In biotechnology, cell growth is one of the most important properties for the characterization and optimization of microbial cultures. Novel live-cell imaging methods are leading to an ever better understanding of cell cultures and their development....

CNN-Pred: Prediction of single-stranded and double-stranded DNA-binding protein using convolutional neural networks.

Gene
DNA-binding proteins play a vital role in biological activity including DNA replication, DNA packing, and DNA reparation. DNA-binding proteins can be classified into single-stranded DNA-binding proteins (SSBs) or double-stranded DNA-binding proteins ...

Early Education Application Software Based on Artificial Intelligence VR Technology.

Computational intelligence and neuroscience
In order to solve the problems of restricted classroom and lack of repeated training in good curriculum, the design and development of a school life adaptation curriculum based on VR is proposed. This study identified six life adaptation themes for d...

Personalized synthetic MR imaging with deep learning enhancements.

Magnetic resonance in medicine
PURPOSE: Personalized synthetic MRI (syn-MRI) uses MR images of an individual subject acquired at a few design parameters (echo time, repetition time, flip angle) to obtain underlying parametric maps, from where MR images of that individual at other...

DrugnomeAI is an ensemble machine-learning framework for predicting druggability of candidate drug targets.

Communications biology
The druggability of targets is a crucial consideration in drug target selection. Here, we adopt a stochastic semi-supervised ML framework to develop DrugnomeAI, which estimates the druggability likelihood for every protein-coding gene in the human ex...

MZA: A Data Conversion Tool to Facilitate Software Development and Artificial Intelligence Research in Multidimensional Mass Spectrometry.

Journal of proteome research
Modern mass spectrometry-based workflows employing hybrid instrumentation and orthogonal separations collect multidimensional data, potentially allowing deeper understanding in omics studies through adoption of artificial intelligence methods. Howeve...

Identification of adaptor proteins by incorporating deep learning and PSSM profiles.

Methods (San Diego, Calif.)
Adaptor proteins, also known as signal transduction adaptor proteins, are important proteins in signal transduction pathways, and play a role in connecting signal proteins for signal transduction between cells. Studies have shown that adaptor protein...

Unified machine learning protocol for copolymer structure-property predictions.

STAR protocols
Structure-property relationships are extremely valuable when predicting the properties of polymers. This protocol demonstrates a step-by-step approach, based on multiple machine learning (ML) architectures, which is capable of processing copolymer ty...