AIMC Topic: Software

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Gene Ontology-Based Analysis of Zebrafish Omics Data Using the Web Tool Comparative Gene Ontology.

Zebrafish
Gene Ontology (GO) analysis is a powerful tool in systems biology, which uses a defined nomenclature to annotate genes/proteins within three categories: "Molecular Function," "Biological Process," and "Cellular Component." GO analysis can assist in r...

EPuL: An Enhanced Positive-Unlabeled Learning Algorithm for the Prediction of Pupylation Sites.

Molecules (Basel, Switzerland)
Protein pupylation is a type of post-translation modification, which plays a crucial role in cellular function of bacterial organisms in prokaryotes. To have a better insight of the mechanisms underlying pupylation an initial, but important, step is ...

Machine learning techniques for the optimization of joint replacements: Application to a short-stem hip implant.

PloS one
Today, different implant designs exist in the market; however, there is not a clear understanding of which are the best implant design parameters to achieve mechanical optimal conditions. Therefore, the aim of this project was to investigate if the g...

Subject-enabled analytics model on measurement statistics in health risk expert system for public health informatics.

International journal of medical informatics
PURPOSE: This study applied open source technology to establish a subject-enabled analytics model that can enhance measurement statistics of case studies with the public health data in cloud computing.

Seizure Classification From EEG Signals Using Transfer Learning, Semi-Supervised Learning and TSK Fuzzy System.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Recognition of epileptic seizures from offline EEG signals is very important in clinical diagnosis of epilepsy. Compared with manual labeling of EEG signals by doctors, machine learning approaches can be faster and more consistent. However, the class...

Breast cancer cell nuclei classification in histopathology images using deep neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: Cell nuclei classification in breast cancer histopathology images plays an important role in effective diagnose since breast cancer can often be characterized by its expression in cell nuclei. However, due to the small and variant sizes of c...

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.

International journal of molecular sciences
Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results i...

The R-package GenomicTools for multifactor dimensionality reduction and the analysis of (exploratory) Quantitative Trait Loci.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: We introduce the R-package GenomicTools to perform, among others, a Multifactor Dimensionality Reduction (MDR) for the identification of SNP-SNP interactions. The package further provides a new class of tests for an (explor...

Convolutional neural networks for automated annotation of cellular cryo-electron tomograms.

Nature methods
Cellular electron cryotomography offers researchers the ability to observe macromolecules frozen in action in situ, but a primary challenge with this technique is identifying molecular components within the crowded cellular environment. We introduce ...

Automatic detection of hemorrhagic pericardial effusion on PMCT using deep learning - a feasibility study.

Forensic science, medicine, and pathology
Post mortem computed tomography (PMCT) can be used as a triage tool to better identify cases with a possibly non-natural cause of death, especially when high caseloads make it impossible to perform autopsies on all cases. Substantial data can be gene...