AIMC Topic: Algorithms

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Network stratification analysis for identifying function-specific network layers.

Molecular bioSystems
A major challenge of systems biology is to capture the rewiring of biological functions (e.g. signaling pathways) in a molecular network. To address this problem, we proposed a novel computational framework, namely network stratification analysis (Ne...

Computer-Aided Endoscopic Diagnosis Without Human-Specific Labeling.

IEEE transactions on bio-medical engineering
GOAL: Most state-of-the-art computer-aided endoscopic diagnosis methods require pixelwise labeled data to train various supervised machine learning models. However, it is a tedious and time-consuming work to collect sufficient precisely labeled image...

Multi-instance multi-label distance metric learning for genome-wide protein function prediction.

Computational biology and chemistry
Multi-instance multi-label (MIML) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with not only multiple instances but also multiple class labels. To find an ...

Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks.

Journal of biomolecular screening
Deep learning methods are currently outperforming traditional state-of-the-art computer vision algorithms in diverse applications and recently even surpassed human performance in object recognition. Here we demonstrate the potential of deep learning ...

Tensor SOM and tensor GTM: Nonlinear tensor analysis by topographic mappings.

Neural networks : the official journal of the International Neural Network Society
In this paper, we propose nonlinear tensor analysis methods: the tensor self-organizing map (TSOM) and the tensor generative topographic mapping (TGTM). TSOM is a straightforward extension of the self-organizing map from high-dimensional data to tens...

Automatic tracking of laparoscopic instruments for autonomous control of a cameraman robot.

Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
BACKGROUND: An automated instrument tracking procedure was designed and developed for autonomous control of a cameraman robot during laparoscopic surgery.

An Inertial Projection Neural Network for Solving Variational Inequalities.

IEEE transactions on cybernetics
Recently, projection neural network (PNN) was proposed for solving monotone variational inequalities (VIs) and related convex optimization problems. In this paper, considering the inertial term into first order PNNs, an inertial PNN (IPNN) is also pr...

Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation.

IEEE transactions on medical imaging
We propose a novel segmentation approach based on deep 3D convolutional encoder networks with shortcut connections and apply it to the segmentation of multiple sclerosis (MS) lesions in magnetic resonance images. Our model is a neural network that co...

Localization and Classification of Paddy Field Pests using a Saliency Map and Deep Convolutional Neural Network.

Scientific reports
We present a pipeline for the visual localization and classification of agricultural pest insects by computing a saliency map and applying deep convolutional neural network (DCNN) learning. First, we used a global contrast region-based approach to co...

Enhancing the Prediction of Transmembrane β-Barrel Segments with Chain Learning and Feature Sparse Representation.

IEEE/ACM transactions on computational biology and bioinformatics
Transmembrane β-barrels (TMBs) are one important class of membrane proteins that play crucial functions in the cell. Membrane proteins are difficult wet-lab targets of structural biology, which call for accurate computational prediction approaches. H...