AIMC Journal:
Methods (San Diego, Calif.)
Showing 161 to 170 of 183 articles
DeepText2GO: Improving large-scale protein function prediction with deep semantic text representation.
Methods (San Diego, Calif.)
Jun 6, 2018
As of April 2018, UniProtKB has collected more than 115 million protein sequences. Less than 0.15% of these proteins, however, have been associated with experimental GO annotations. As such, the use of automatic protein function prediction (AFP) to r...
Leveraging multiple gene networks to prioritize GWAS candidate genes via network representation learning.
Methods (San Diego, Calif.)
Jun 3, 2018
Genome-wide association studies (GWAS) have successfully discovered a number of disease-associated genetic variants in the past decade, providing an unprecedented opportunity for deciphering genetic basis of human inherited diseases. However, it is s...
Affinity network fusion and semi-supervised learning for cancer patient clustering.
Methods (San Diego, Calif.)
May 26, 2018
Defining subtypes of complex diseases such as cancer and stratifying patient groups with the same disease but different subtypes for targeted treatments is important for personalized and precision medicine. Approaches that incorporate multi-omic data...
Large-scale machine learning of media outlets for understanding public reactions to nation-wide viral infection outbreaks.
Methods (San Diego, Calif.)
Aug 13, 2017
From May to July 2015, there was a nation-wide outbreak of Middle East respiratory syndrome (MERS) in Korea. MERS is caused by MERS-CoV, an enveloped, positive-sense, single-stranded RNA virus belonging to the family Coronaviridae. Despite expert opi...
A machine learning approach for automated wide-range frequency tagging analysis in embedded neuromonitoring systems.
Methods (San Diego, Calif.)
Jun 22, 2017
EEG is a standard non-invasive technique used in neural disease diagnostics and neurosciences. Frequency-tagging is an increasingly popular experimental paradigm that efficiently tests brain function by measuring EEG responses to periodic stimulation...
Analysis of live cell images: Methods, tools and opportunities.
Methods (San Diego, Calif.)
Feb 27, 2017
Advances in optical microscopy, biosensors and cell culturing technologies have transformed live cell imaging. Thanks to these advances live cell imaging plays an increasingly important role in basic biology research as well as at all stages of drug ...
Interactive Exploration for Continuously Expanding Neuron Databases.
Methods (San Diego, Calif.)
Feb 17, 2017
This paper proposes a novel framework to help biologists explore and analyze neurons based on retrieval of data from neuron morphological databases. In recent years, the continuously expanding neuron databases provide a rich source of information to ...
TED: A Tolerant Edit Distance for segmentation evaluation.
Methods (San Diego, Calif.)
Jan 17, 2017
In this paper, we present a novel error measure to compare a computer-generated segmentation of images or volumes against ground truth. This measure, which we call Tolerant Edit Distance (TED), is motivated by two observations that we usually encount...
An Overview of data science uses in bioimage informatics.
Methods (San Diego, Calif.)
Jan 3, 2017
This review aims at providing a practical overview of the use of statistical features and associated data science methods in bioimage informatics. To achieve a quantitative link between images and biological concepts, one typically replaces an object...
An open-source solution for advanced imaging flow cytometry data analysis using machine learning.
Methods (San Diego, Calif.)
Sep 2, 2016
Imaging flow cytometry (IFC) enables the high throughput collection of morphological and spatial information from hundreds of thousands of single cells. This high content, information rich image data can in theory resolve important biological differe...
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