AIMC Topic: Computational Biology

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Brain-Wide Genome-Wide Association Study for Alzheimer's Disease via Joint Projection Learning and Sparse Regression Model.

IEEE transactions on bio-medical engineering
Brain-wide and genome-wide association (BW-GWA) study is presented in this paper to identify the associations between the brain imaging phenotypes (i.e., regional volumetric measures) and the genetic variants [i.e., single nucleotide polymorphism (SN...

Artificial neural network model for predicting the bioavailability of tacrolimus in patients with renal transplantation.

PloS one
The objective of the current study was to explore the role of ABCB1 and CYP3A5 genetic polymorphisms in predicting the bioavailability of tacrolimus and the risk for post-transplant diabetes. Artificial neural network (ANN) and logistic regression (L...

Transfer Learning for Molecular Cancer Classification Using Deep Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics
The emergence of deep learning has impacted numerous machine learning based applications and research. The reason for its success lies in two main advantages: 1) it provides the ability to learn very complex non-linear relationships between features ...

AdaSampling for Positive-Unlabeled and Label Noise Learning With Bioinformatics Applications.

IEEE transactions on cybernetics
Class labels are required for supervised learning but may be corrupted or missing in various applications. In binary classification, for example, when only a subset of positive instances is labeled whereas the remaining are unlabeled, positive-unlabe...

Modified Global Flower Pollination Algorithm and its Application for Optimization Problems.

Interdisciplinary sciences, computational life sciences
Flower Pollination Algorithm (FPA) has increasingly attracted researchers' attention in the computational intelligence field. This is due to its simplicity and efficiency in searching for global optimality of many optimization problems. However, ther...

Sequential regulatory activity prediction across chromosomes with convolutional neural networks.

Genome research
Models for predicting phenotypic outcomes from genotypes have important applications to understanding genomic function and improving human health. Here, we develop a machine-learning system to predict cell-type-specific epigenetic and transcriptional...

High-Order Convolutional Neural Network Architecture for Predicting DNA-Protein Binding Sites.

IEEE/ACM transactions on computational biology and bioinformatics
Although Deep learning algorithms have outperformed conventional methods in predicting the sequence specificities of DNA-protein binding, they lack to consider the dependencies among nucleotides and the diverse binding lengths for different transcrip...

HMMER Cut-off Threshold Tool (HMMERCTTER): Supervised classification of superfamily protein sequences with a reliable cut-off threshold.

PloS one
BACKGROUND: Protein superfamilies can be divided into subfamilies of proteins with different functional characteristics. Their sequences can be classified hierarchically, which is part of sequence function assignation. Typically, there are no clear s...

Interpretation of biological experiments changes with evolution of the Gene Ontology and its annotations.

Scientific reports
Gene Ontology (GO) enrichment analysis is ubiquitously used for interpreting high throughput molecular data and generating hypotheses about underlying biological phenomena of experiments. However, the two building blocks of this analysis - the ontolo...

Prediction of influenza-like illness based on the improved artificial tree algorithm and artificial neural network.

Scientific reports
Because influenza is a contagious respiratory illness that seriously threatens public health, accurate real-time prediction of influenza outbreaks may help save lives. In this paper, we use the Twitter data set and the United States Centers for Disea...