AIMC Topic: Machine Learning

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Nano Random Forests to mine protein complexes and their relationships in quantitative proteomics data.

Molecular biology of the cell
Ever-increasing numbers of quantitative proteomics data sets constitute an underexploited resource for investigating protein function. Multiprotein complexes often follow consistent trends in these experiments, which could provide insights about thei...

Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model.

PLoS computational biology
MOTIVATION: Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predict...

PaPrBaG: A machine learning approach for the detection of novel pathogens from NGS data.

Scientific reports
The reliable detection of novel bacterial pathogens from next-generation sequencing data is a key challenge for microbial diagnostics. Current computational tools usually rely on sequence similarity and often fail to detect novel species when closely...

Constructing a meta-tracker using Dropout to imitate the behavior of an arbitrary black-box tracker.

Neural networks : the official journal of the International Neural Network Society
Imitating the behaviors of an arbitrary visual tracking algorithm enables many higher level tasks such as tracker identification and efficient tracker-fusion. It is also useful for discovering the features essential in a black-box tracker or learning...

An Overview of data science uses in bioimage informatics.

Methods (San Diego, Calif.)
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...

Prediction of cold and heat patterns using anthropometric measures based on machine learning.

Chinese journal of integrative medicine
OBJECTIVE: To examine the association of body shape with cold and heat patterns, to determine which anthropometric measure is the best indicator for discriminating between the two patterns, and to investigate whether using a combination of measures c...

Efficient Approach for RLS Type Learning in TSK Neural Fuzzy Systems.

IEEE transactions on cybernetics
This paper presents an efficient approach for the use of recursive least square (RLS) learning algorithm in Takagi-Sugeno-Kang neural fuzzy systems. In the use of RLS, reduced covariance matrix, of which the off-diagonal blocks defining the correlati...

Machine Learning Methods to Predict Density Functional Theory B3LYP Energies of HOMO and LUMO Orbitals.

Journal of chemical information and modeling
Machine learning algorithms were explored for the fast estimation of HOMO and LUMO orbital energies calculated by DFT B3LYP, on the basis of molecular descriptors exclusively based on connectivity. The whole project involved the retrieval and generat...

Deep Learning for Health Informatics.

IEEE journal of biomedical and health informatics
With a massive influx of multimodality data, the role of data analytics in health informatics has grown rapidly in the last decade. This has also prompted increasing interests in the generation of analytical, data driven models based on machine learn...