AIMC Topic: Datasets as Topic

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ME-Class2 reveals context dependent regulatory roles for 5-hydroxymethylcytosine.

Nucleic acids research
Since the discovery of 5-hydroxymethylcytosine (5hmC) as a prominent DNA modification found in mammalian genomes, an emergent question has been what role this mark plays in gene regulation. 5hmC is hypothesized to function as an intermediate in the d...

Machine Learning as an Effective Method for Identifying True Single Nucleotide Polymorphisms in Polyploid Plants.

The plant genome
Single nucleotide polymorphisms (SNPs) have many advantages as molecular markers since they are ubiquitous and codominant. However, the discovery of true SNPs in polyploid species is difficult. Peanut ( L.) is an allopolyploid, which has a very low r...

Classifying relations in clinical narratives using segment graph convolutional and recurrent neural networks (Seg-GCRNs).

Journal of the American Medical Informatics Association : JAMIA
We propose to use segment graph convolutional and recurrent neural networks (Seg-GCRNs), which use only word embedding and sentence syntactic dependencies, to classify relations from clinical notes without manual feature engineering. In this study, t...

Synthesizing electronic health records using improved generative adversarial networks.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The aim of this study was to generate synthetic electronic health records (EHRs). The generated EHR data will be more realistic than those generated using the existing medical Generative Adversarial Network (medGAN) method.

Machine Learning: Advanced Image Segmentation Using ilastik.

Methods in molecular biology (Clifton, N.J.)
Segmentation is one of the most ubiquitous problems in biological image analysis. Here we present a machine learning-based solution to it as implemented in the open source ilastik toolkit. We give a broad description of the underlying theory and demo...

A Cell Segmentation/Tracking Tool Based on Machine Learning.

Methods in molecular biology (Clifton, N.J.)
The ability to gain quantifiable, single-cell data from time-lapse microscopy images is dependent upon cell segmentation and tracking. Here, we present a detailed protocol for obtaining quality time-lapse movies and introduce a method to identify (se...

Unsupervised GRN Ensemble.

Methods in molecular biology (Clifton, N.J.)
Inferring gene regulatory networks from expression data is a very challenging problem that has raised the interest of the scientific community. Different algorithms have been proposed to try to solve this issue, but it has been shown that different m...

Expert-level sleep scoring with deep neural networks.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Scoring laboratory polysomnography (PSG) data remains a manual task of visually annotating 3 primary categories: sleep stages, sleep disordered breathing, and limb movements. Attempts to automate this process have been hampered by the com...