Genetics

Latent space of a small genetic network: Geometry of dynamics and information.

The high-dimensional character of most biological systems presents genuine challenges for modeling and prediction. Here we propose a neural network-based approach for dimensionality reduction and analysis of biological gene expression data, using, as a case study, a well-known genetic network in the early embryo, the gap gene patterning system. We build an autoencoder compressing the dynamics of ...

A Robust Deep Neural Network for Rolling Element Fault Diagnosis under Various Operating and Noisy Conditions.

This study proposes a new intelligent diagnostic method for bearing faults in rotating machinery. The method uses a combination of nonlinear mode decomposition based on the improved fast kurtogram, gramian angular field, and convolutional neural network to detect the bearing state of rotating machinery. The nonlinear mode decomposition based on the improved fast kurtogram inherits the advantages o...

Boosted Sine Cosine Algorithm with Application to Medical Diagnosis.

The sine cosine algorithm (SCA) was proposed for solving optimization tasks, of which the way to obtain the optimal solution is mainly through the con...

Codon Optimization Using a Recurrent Neural Network.

Codon optimization of a DNA sequence can significantly increase efficiency of protein expression, reducing the cost to manufacture biologic pharmaceut...

DeepRF: A deep learning method for predicting metabolic pathways in organisms based on annotated genomes.

The rapid increase of metabolomics has led to an increasing focus on metabolic pathway modeling and reconstruction. In particular, reconstructing an o...

Combined artificial intelligence and radiologist model for predicting rectal cancer treatment response from magnetic resonance imaging: an external validation study.

PURPOSE: To evaluate an MRI-based radiomic texture classifier alone and combined with radiologist qualitative assessment in predicting pathological co...

Systems Drug Discovery for Diffuse Large B Cell Lymphoma Based on Pathogenic Molecular Mechanism via Big Data Mining and Deep Learning Method.

Diffuse large B cell lymphoma (DLBCL) is an aggressive heterogeneous disease. The most common subtypes of DLBCL include germinal center b-cell (GCB) t...

Improved Analysis of COVID-19 Influenced Pneumonia from the Chest X-Rays Using Fine-Tuned Residual Networks.

COVID-19 has remained a threat to world life despite a recent reduction in cases. There is still a possibility that the virus will evolve and become m...

Machine Learning Guided Batched Design of a Bacterial Ribosome Binding Site.

Optimization of gene expression levels is an essential part of the organism design process. Fine control of this process can be achieved by engineerin...

Polishing copy number variant calls on exome sequencing data via deep learning.

Accurate and efficient detection of copy number variants (CNVs) is of critical importance owing to their significant association with complex genetic ...

Single-Cell Sequencing Analysis and Multiple Machine Learning Methods Identified G0S2 and HPSE as Novel Biomarkers for Abdominal Aortic Aneurysm.

Identifying biomarkers for abdominal aortic aneurysms (AAA) is key to understanding their pathogenesis, developing novel targeted therapeutics, and po...

Image super-resolution with an enhanced group convolutional neural network.

CNNs with strong learning abilities are widely chosen to resolve super-resolution problem. However, CNNs depend on deeper network architectures to imp...

Can machines learn the mutation signatures of SARS-CoV-2 and enable viral-genotype guided predictive prognosis?

MOTIVATION: Continuous emergence of new variants through appearance/accumulation/disappearance of mutations is a hallmark of many viral diseases. SARS...

A deep learning model to classify neoplastic state and tissue origin from transcriptomic data.

Application of deep learning methods to transcriptomic data has the potential to enhance the accuracy and efficiency of tissue classification and cell...

Using deep learning to detect digitally encoded DNA trigger for Trojan malware in Bio-Cyber attacks.

This article uses Deep Learning technologies to safeguard DNA sequencing against Bio-Cyber attacks. We consider a hybrid attack scenario where the pay...

Mathematical approach for segmenting chromosome clusters in metaspread images.

Karyotyping is an examination that helps in detecting chromosomal abnormalities. Chromosome analysis is a very challenging task which requires various...

Generalized genomic data sharing for differentially private federated learning.

The success behind Machine Learning (ML) methods has largely been attributed to the quality and quantity of the available data which can spread across...

Multiclass Cancer Prediction Based on Copy Number Variation Using Deep Learning.

DNA copy number variation (CNV) is the type of DNA variation which is associated with various human diseases. CNV ranges in size from 1 kilobase to se...

Deep learning-based transcription factor activity for stratification of breast cancer patients.

Transcription factors directly bind to DNA and regulate the expression of the gene, causing epigenetic modification of the DNA. They often mediate epi...

STEM Image Analysis Based on Deep Learning: Identification of Vacancy Defects and Polymorphs of MoS.

Scanning transmission electron microscopy (STEM) is an indispensable tool for atomic-resolution structural analysis for a wide range of materials. The...