Genetics

Transforming L1000 profiles to RNA-seq-like profiles with deep learning.

The L1000 technology, a cost-effective high-throughput transcriptomics technology, has been applied to profile a collection of human cell lines for their gene expression response to > 30,000 chemical and genetic perturbations. In total, there are currently over 3 million available L1000 profiles. Such a dataset is invaluable for the discovery of drug and target candidates and for inferring mechani...

A Fast Decision Algorithm for VVC Intra-Coding Based on Texture Feature and Machine Learning.

Due to the development and application of information technology, a series of modern information technologies represented by 5G, big data, and artificial intelligence are changing rapidly, and people's requirements for video coding standards have become higher. In the High-Efficiency Video Coding (HEVC) standard, the coding block division is not flexible enough, and the prediction mode is not deta...

TAMC: A deep-learning approach to predict motif-centric transcriptional factor binding activity based on ATAC-seq profile.

Determining transcriptional factor binding sites (TFBSs) is critical for understanding the molecular mechanisms regulating gene expression in differen...

Identification of Unique Genetic Biomarkers of Various Subtypes of Glomerulonephritis Using Machine Learning and Deep Learning.

(1) Objective: Identification of potential genetic biomarkers for various glomerulonephritis (GN) subtypes and discovering the molecular mechanisms of...

Identification of DNA-binding proteins via Multi-view LSSVM with independence criterion.

DNA-binding proteins actively participate in life activities such as DNA replication, recombination, gene expression and regulation and play a promine...

Multinomial Convolutions for Joint Modeling of Regulatory Motifs and Sequence Activity Readouts.

A common goal in the convolutional neural network (CNN) modeling of genomic data is to discover specific sequence motifs. Post hoc analysis methods ai...

A Study on the Prediction of Cancer Using Whole-Genome Data and Deep Learning.

The number of patients diagnosed with cancer continues to increasingly rise, and has nearly doubled in 20 years. Therefore, predicting cancer occurren...

Identifying Drug Targets of Oral Squamous Cell Carcinoma through a Systems Biology Method and Genome-Wide Microarray Data for Drug Discovery by Deep Learning and Drug Design Specifications.

In this study, we provide a systems biology method to investigate the carcinogenic mechanism of oral squamous cell carcinoma (OSCC) in order to identi...

Smart breeding driven by big data, artificial intelligence, and integrated genomic-enviromic prediction.

The first paradigm of plant breeding involves direct selection-based phenotypic observation, followed by predictive breeding using statistical models ...

A machine learning technique for identifying DNA enhancer regions utilizing CIS-regulatory element patterns.

Enhancers regulate gene expression, by playing a crucial role in the synthesis of RNAs and proteins. They do not directly encode proteins or RNA molec...

Effectiveness Assessment of College Ideological and Political Courses Using BP Neural Networks in Network Environment.

We will not be able to provide educators with the assistance they require to implement the network IPECU and boost the effectiveness of the network IP...

Direct identification of ALK and ROS1 fusions in non-small cell lung cancer from hematoxylin and eosin-stained slides using deep learning algorithms.

Anaplastic lymphoma kinase (ALK) and ROS oncogene 1 (ROS1) gene fusions are well-established key players in non-small cell lung cancer (NSCLC). Althou...

BAT-Net: An enhanced RNA Secondary Structure prediction via bidirectional GRU-based network with attention mechanism.

BACKGROUND: RNA Secondary Structure (RSS) has drawn growing concern, both for their pivotal roles in RNA tertiary structures prediction and critical e...

Quartet Based Gene Tree Imputation Using Deep Learning Improves Phylogenomic Analyses Despite Missing Data.

Species tree estimation is frequently based on phylogenomic approaches that use multiple genes from throughout the genome. However, for a combination ...

One shot ancient character recognition with siamese similarity network.

Ancient character recognition is not only important for the study and understanding of ancient history but also has a profound impact on the inheritan...

A Gradient-Guided Evolutionary Approach to Training Deep Neural Networks.

It has been widely recognized that the efficient training of neural networks (NNs) is crucial to classification performance. While a series of gradien...

Analysis of the Effects of Arts and Crafts in Public Mental Health Education Based on Artificial Intelligence Technology.

Arts and crafts, with their very different styles due to many factors such as times, regions, technologies, and cultures and nationalities, have under...

-Complex-Based Machine Learning (HCML) for the Prediction of Protein-Protein Binding Affinity Changes upon Mutation.

Protein-protein interactions (PPIs) are involved in almost all biological processes in the cell. Understanding protein-protein interactions holds the ...

Improving the prediction of DNA-protein binding by integrating multi-scale dense convolutional network with fault-tolerant coding.

Accurate prediction of DNA-protein binding (DPB) is of great biological significance for studying the regulatory mechanism of gene expression. In rece...

Towards computational solutions for precision medicine based big data healthcare system using deep learning models: A review.

The emergence of large-scale human genome projects, advances in DNA sequencing technologies, and the massive volume of electronic medical records [EMR...