AIMC Topic: Software

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PeptiDesCalculator: Software for computation of peptide descriptors. Definition, implementation and case studies for 9 bioactivity endpoints.

Proteins
We present a novel Java-based program denominated PeptiDesCalculator for computing peptide descriptors. These descriptors include: redefinitions of known protein parameters to suite the peptide domain, generalization schemes for the global descriptio...

Self-grouping convolutional neural networks.

Neural networks : the official journal of the International Neural Network Society
Although group convolution operators are increasingly used in deep convolutional neural networks to improve the computational efficiency and to reduce the number of parameters, most existing methods construct their group convolution architectures by ...

DNSS2: Improved ab initio protein secondary structure prediction using advanced deep learning architectures.

Proteins
Accurate prediction of protein secondary structure (alpha-helix, beta-strand and coil) is a crucial step for protein inter-residue contact prediction and ab initio tertiary structure prediction. In a previous study, we developed a deep belief network...

Emulating Docking Results Using a Deep Neural Network: A New Perspective for Virtual Screening.

Journal of chemical information and modeling
Docking is one of the most important steps in virtual screening pipelines, and it is an established method for examining potential interactions between ligands and receptors. However, this method is computationally expensive, and it is often among th...

A Web Application for Adrenal Incidentaloma Identification, Tracking, and Management Using Machine Learning.

Applied clinical informatics
BACKGROUND: Incidental radiographic findings, such as adrenal nodules, are commonly identified in imaging studies and documented in radiology reports. However, patients with such findings frequently do not receive appropriate follow-up, partially due...

NuSeT: A deep learning tool for reliably separating and analyzing crowded cells.

PLoS computational biology
Segmenting cell nuclei within microscopy images is a ubiquitous task in biological research and clinical applications. Unfortunately, segmenting low-contrast overlapping objects that may be tightly packed is a major bottleneck in standard deep learni...

Accurate prediction of DNA N-methylcytosine sites via boost-learning various types of sequence features.

BMC genomics
BACKGROUND: DNA N4-methylcytosine (4mC) is a critical epigenetic modification and has various roles in the restriction-modification system. Due to the high cost of experimental laboratory detection, computational methods using sequence characteristic...

Accurate deep neural network model to detect cardiac arrhythmia on more than 10,000 individual subject ECG records.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Cardiac arrhythmia, which is an abnormal heart rhythm, is a common clinical problem in cardiology. Detection of arrhythmia on an extended duration electrocardiogram (ECG) is done based on initial algorithmic software screeni...

ODiNPred: comprehensive prediction of protein order and disorder.

Scientific reports
Structural disorder is widespread in eukaryotic proteins and is vital for their function in diverse biological processes. It is therefore highly desirable to be able to predict the degree of order and disorder from amino acid sequence. It is, however...

MosaicBase: A Knowledgebase of Postzygotic Mosaic Variants in Noncancer Disease-related and Healthy Human Individuals.

Genomics, proteomics & bioinformatics
Mosaic variants resulting from postzygotic mutations are prevalent in the human genome and play important roles in human diseases. However, except for cancer-related variants, there is no collection of postzygotic mosaic variants in noncancer disease...