AIMC Topic: Machine Learning

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Predicting enhancers with deep convolutional neural networks.

BMC bioinformatics
BACKGROUND: With the rapid development of deep sequencing techniques in the recent years, enhancers have been systematically identified in such projects as FANTOM and ENCODE, forming genome-wide landscapes in a series of human cell lines. Nevertheles...

Exploring the Impact of Food on the Gut Ecosystem Based on the Combination of Machine Learning and Network Visualization.

Nutrients
Prebiotics and probiotics strongly impact the gut ecosystem by changing the composition and/or metabolism of the microbiota to improve the health of the host. However, the composition of the microbiota constantly changes due to the intake of daily di...

Medical subdomain classification of clinical notes using a machine learning-based natural language processing approach.

BMC medical informatics and decision making
BACKGROUND: The medical subdomain of a clinical note, such as cardiology or neurology, is useful content-derived metadata for developing machine learning downstream applications. To classify the medical subdomain of a note accurately, we have constru...

Decontaminating eukaryotic genome assemblies with machine learning.

BMC bioinformatics
BACKGROUND: High-throughput sequencing has made it theoretically possible to obtain high-quality de novo assembled genome sequences but in practice DNA extracts are often contaminated with sequences from other organisms. Currently, there are few exis...

Assessment of the model refinement category in CASP12.

Proteins
We here report on the assessment of the model refinement predictions submitted to the 12th Experiment on the Critical Assessment of Protein Structure Prediction (CASP12). This is the fifth refinement experiment since CASP8 (2008) and, as with the pre...

Large-scale automated function prediction of protein sequences and an experimental case study validation on PTEN transcript variants.

Proteins
Recent advances in computing power and machine learning empower functional annotation of protein sequences and their transcript variations. Here, we present an automated prediction system UniGOPred, for GO annotations and a database of GO term predic...

Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States.

Proceedings of the National Academy of Sciences of the United States of America
The United States spends more than $250 million each year on the American Community Survey (ACS), a labor-intensive door-to-door study that measures statistics relating to race, gender, education, occupation, unemployment, and other demographic facto...

A systematic review of data mining and machine learning for air pollution epidemiology.

BMC public health
BACKGROUND: Data measuring airborne pollutants, public health and environmental factors are increasingly being stored and merged. These big datasets offer great potential, but also challenge traditional epidemiological methods. This has motivated the...

Ensemble machine learning and forecasting can achieve 99% uptime for rural handpumps.

PloS one
Broken water pumps continue to impede efforts to deliver clean and economically-viable water to the global poor. The literature has demonstrated that customers' health benefits and willingness to pay for clean water are best realized when clean water...

A Treatment-Response Index From Wearable Sensors for Quantifying Parkinson's Disease Motor States.

IEEE journal of biomedical and health informatics
The goal of this study was to develop an algorithm that automatically quantifies motor states (off, on, dyskinesia) in Parkinson's disease (PD), based on accelerometry during a hand pronation-supination test. Clinician's ratings using the Treatment R...