AIMC Topic: Computational Biology

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Reconstructing cancer drug response networks using multitask learning.

BMC systems biology
BACKGROUND: Translating in vitro results to clinical tests is a major challenge in systems biology. Here we present a new Multi-Task learning framework which integrates thousands of cell line expression experiments to reconstruct drug specific respon...

Unified Deep Learning Architecture for Modeling Biology Sequence.

IEEE/ACM transactions on computational biology and bioinformatics
Prediction of the spatial structure or function of biological macromolecules based on their sequences remains an important challenge in bioinformatics. When modeling biological sequences using traditional sequencing models, long-range interaction, co...

Deep Learning-Based Multi-Omics Integration Robustly Predicts Survival in Liver Cancer.

Clinical cancer research : an official journal of the American Association for Cancer Research
Identifying robust survival subgroups of hepatocellular carcinoma (HCC) will significantly improve patient care. Currently, endeavor of integrating multi-omics data to explicitly predict HCC survival from multiple patient cohorts is lacking. To fill ...

SNAVA-A real-time multi-FPGA multi-model spiking neural network simulation architecture.

Neural networks : the official journal of the International Neural Network Society
Spiking Neural Networks (SNN) for Versatile Applications (SNAVA) simulation platform is a scalable and programmable parallel architecture that supports real-time, large-scale, multi-model SNN computation. This parallel architecture is implemented in ...

DRREP: deep ridge regressed epitope predictor.

BMC genomics
INTRODUCTION: The ability to predict epitopes plays an enormous role in vaccine development in terms of our ability to zero in on where to do a more thorough in-vivo analysis of the protein in question. Though for the past decade there have been nume...

Improved protein contact predictions with the MetaPSICOV2 server in CASP12.

Proteins
In this paper, we present the results for the MetaPSICOV2 contact prediction server in the CASP12 community experiment (http://predictioncenter.org). Over the 35 assessed Free Modelling target domains the MetaPSICOV2 server achieved a mean precision ...

Multi-layer network utilizing rewarded spike time dependent plasticity to learn a foraging task.

PLoS computational biology
Neural networks with a single plastic layer employing reward modulated spike time dependent plasticity (STDP) are capable of learning simple foraging tasks. Here we demonstrate advanced pattern discrimination and continuous learning in a network of s...

Mimvec: a deep learning approach for analyzing the human phenome.

BMC systems biology
BACKGROUND: The human phenome has been widely used with a variety of genomic data sources in the inference of disease genes. However, most existing methods thus far derive phenotype similarity based on the analysis of biomedical databases by using th...

NetGen: a novel network-based probabilistic generative model for gene set functional enrichment analysis.

BMC systems biology
BACKGROUND: High-throughput experimental techniques have been dramatically improved and widely applied in the past decades. However, biological interpretation of the high-throughput experimental results, such as differential expression gene sets deri...

A novel method to identify pre-microRNA in various species knowledge base on various species.

Journal of biomedical semantics
BACKGROUND: More than 1/3 of human genes are regulated by microRNAs. The identification of microRNA (miRNA) is the precondition of discovering the regulatory mechanism of miRNA and developing the cure for genetic diseases. The traditional identificat...