AIMC Topic: Computational Biology

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Deep Learning for Automated Feature Discovery and Classification of Sleep Stages.

IEEE/ACM transactions on computational biology and bioinformatics
Convolutional neural networks (CNN) have demonstrated state-of-the-art classification results in image categorization, but have received comparatively little attention for classification of one-dimensional physiological signals. We design a deep CNN ...

Deep Learning Benchmarks on L1000 Gene Expression Data.

IEEE/ACM transactions on computational biology and bioinformatics
Gene expression data can offer deep, physiological insights beyond the static coding of the genome alone. We believe that realizing this potential requires specialized, high-capacity machine learning methods capable of using underlying biological str...

Extracting Inter-Sentence Relations for Associating Biological Context with Events in Biomedical Texts.

IEEE/ACM transactions on computational biology and bioinformatics
We present an analysis of the problem of identifying biological context and associating it with biochemical events described in biomedical texts. This constitutes a non-trivial, inter-sentential relation extraction task. We focus on biological contex...

Establishment of a morphological atlas of the Caenorhabditis elegans embryo using deep-learning-based 4D segmentation.

Nature communications
The invariant development and transparent body of the nematode Caenorhabditis elegans enables complete delineation of cell lineages throughout development. Despite extensive studies of cell division, cell migration and cell fate differentiation, cell...

Tackling the challenges of bioimage analysis.

eLife
Using multiple human annotators and ensembles of trained networks can improve the performance of deep-learning methods in research.

How to Determine the Early Warning Threshold Value of Meteorological Factors on Influenza through Big Data Analysis and Machine Learning.

Computational and mathematical methods in medicine
Infectious diseases are a major health challenge for the worldwide population. Since their rapid spread can cause great distress to the real world, in addition to taking appropriate measures to curb the spread of infectious diseases in the event of a...

Predicting changes in protein thermodynamic stability upon point mutation with deep 3D convolutional neural networks.

PLoS computational biology
Predicting mutation-induced changes in protein thermodynamic stability (ΔΔG) is of great interest in protein engineering, variant interpretation, and protein biophysics. We introduce ThermoNet, a deep, 3D-convolutional neural network (3D-CNN) designe...

PupStruct: Prediction of Pupylated Lysine Residues Using Structural Properties of Amino Acids.

Genes
Post-translational modification (PTM) is a critical biological reaction which adds to the diversification of the proteome. With numerous known modifications being studied, pupylation has gained focus in the scientific community due to its significant...