AIMC Topic: Computational Biology

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Automated detection of COVID-19 cases using deep neural networks with X-ray images.

Computers in biology and medicine
The novel coronavirus 2019 (COVID-2019), which first appeared in Wuhan city of China in December 2019, spread rapidly around the world and became a pandemic. It has caused a devastating effect on both daily lives, public health, and the global econom...

AFP-LSE: Antifreeze Proteins Prediction Using Latent Space Encoding of Composition of k-Spaced Amino Acid Pairs.

Scientific reports
Species living in extremely cold environments resist the freezing conditions through antifreeze proteins (AFPs). Apart from being essential proteins for various organisms living in sub-zero temperatures, AFPs have numerous applications in different i...

Anomaly Detection-Based Recognition of Near-Native Protein Structures.

IEEE transactions on nanobioscience
The three-dimensional structures populated by a protein molecule determine to a great extent its biological activities. The rich information encoded by protein structure on protein function continues to motivate the development of computational appro...

ASAP-SML: An antibody sequence analysis pipeline using statistical testing and machine learning.

PLoS computational biology
Antibodies are capable of potently and specifically binding individual antigens and, in some cases, disrupting their functions. The key challenge in generating antibody-based inhibitors is the lack of fundamental information relating sequences of ant...

Decentralized control of insect walking: A simple neural network explains a wide range of behavioral and neurophysiological results.

PLoS computational biology
Controlling the six legs of an insect walking in an unpredictable environment is a challenging task, as many degrees of freedom have to be coordinated. Solutions proposed to deal with this task are usually based on the highly influential concept that...

Dual graph convolutional neural network for predicting chemical networks.

BMC bioinformatics
BACKGROUND: Predicting of chemical compounds is one of the fundamental tasks in bioinformatics and chemoinformatics, because it contributes to various applications in metabolic engineering and drug discovery. The recent rapid growth of the amount of ...

TooT-T: discrimination of transport proteins from non-transport proteins.

BMC bioinformatics
BACKGROUND: Membrane transport proteins (transporters) play an essential role in every living cell by transporting hydrophilic molecules across the hydrophobic membranes. While the sequences of many membrane proteins are known, their structure and fu...

BioConceptVec: Creating and evaluating literature-based biomedical concept embeddings on a large scale.

PLoS computational biology
A massive number of biological entities, such as genes and mutations, are mentioned in the biomedical literature. The capturing of the semantic relatedness of biological entities is vital to many biological applications, such as protein-protein inter...

Target Identification Using Homopharma and Network-Based Methods for Predicting Compounds Against Dengue Virus-Infected Cells.

Molecules (Basel, Switzerland)
Drug target prediction is an important method for drug discovery and design, can disclose the potential inhibitory effect of active compounds, and is particularly relevant to many diseases that have the potential to kill, such as dengue, but lack any...

Opening the Black Box: Interpretable Machine Learning for Geneticists.

Trends in genetics : TIG
Because of its ability to find complex patterns in high dimensional and heterogeneous data, machine learning (ML) has emerged as a critical tool for making sense of the growing amount of genetic and genomic data available. While the complexity of ML ...