AIMC Topic: Software

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Protein threading using residue co-variation and deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Template-based modeling, including homology modeling and protein threading, is a popular method for protein 3D structure prediction. However, alignment generation and template selection for protein sequences without close templates remain...

Classifying tumors by supervised network propagation.

Bioinformatics (Oxford, England)
MOTIVATION: Network propagation has been widely used to aggregate and amplify the effects of tumor mutations using knowledge of molecular interaction networks. However, propagating mutations through interactions irrelevant to cancer leads to erosion ...

Convolutional neural networks for classification of alignments of non-coding RNA sequences.

Bioinformatics (Oxford, England)
MOTIVATION: The convolutional neural network (CNN) has been applied to the classification problem of DNA sequences, with the additional purpose of motif discovery. The training of CNNs with distributed representations of four nucleotides has successf...

Learning with multiple pairwise kernels for drug bioactivity prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Many inference problems in bioinformatics, including drug bioactivity prediction, can be formulated as pairwise learning problems, in which one is interested in making predictions for pairs of objects, e.g. drugs and their targets. Kernel...

Gene prioritization using Bayesian matrix factorization with genomic and phenotypic side information.

Bioinformatics (Oxford, England)
MOTIVATION: Most gene prioritization methods model each disease or phenotype individually, but this fails to capture patterns common to several diseases or phenotypes. To overcome this limitation, we formulate the gene prioritization task as the fact...

DeepFam: deep learning based alignment-free method for protein family modeling and prediction.

Bioinformatics (Oxford, England)
MOTIVATION: A large number of newly sequenced proteins are generated by the next-generation sequencing technologies and the biochemical function assignment of the proteins is an important task. However, biological experiments are too expensive to cha...

COSSMO: predicting competitive alternative splice site selection using deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Alternative splice site selection is inherently competitive and the probability of a given splice site to be used also depends on the strength of neighboring sites. Here, we present a new model named the competitive splice site model (COS...

Automatic recognition of holistic functional brain networks using iteratively optimized convolutional neural networks (IO-CNN) with weak label initialization.

Medical image analysis
fMRI data decomposition techniques have advanced significantly from shallow models such as Independent Component Analysis (ICA) and Sparse Coding and Dictionary Learning (SCDL) to deep learning models such Deep Belief Networks (DBN) and Convolutional...

pBRIT: gene prioritization by correlating functional and phenotypic annotations through integrative data fusion.

Bioinformatics (Oxford, England)
MOTIVATION: Computational gene prioritization can aid in disease gene identification. Here, we propose pBRIT (prioritization using Bayesian Ridge regression and Information Theoretic model), a novel adaptive and scalable prioritization tool, integrat...