Fungal gene predictionFungal genome annotation pipelineGenome annotationGenome assemblyRNA-seqFunGAP is a Python-wrapped fungal genome annotation pipeline running under the Linux/Unix operating system. The annotation procedure used in FunGAP requires two inputs, genome assembly and RNA-seq reads. FunGAP...
and critical downstream applications in human genetics depend on improved solutions. Here, we report substantially improved gene expression prediction accuracy from DNA sequences through the use of a deep learning architecture, called Enformer, that is able to integrate information from long-...
严格来说,标记基因选择是DE基因鉴定的一个子集,有效且有用的标记基因具有并非所有DE基因所共有的特定特征。广义上,我们将标记基因定义为可用于区分细胞亚群的基因。 文献标题及背景 A comparison of marker gene selection methods for single‑cell RNA sequencing data. 背景:分析 scRNA-seq 数据的一个常见步骤是...
Spectra also uncovered cell-type-specific expression of amino acid factors, such as lysine metabolism in plasma cells (Fig.4a). Lysine is a scarce nutrient in malignant breast cancer tissue43. Lysine metabolism scored high in Spectra’s information and importance scores (Extended Data Fig.7a). I...
PProdigal: Parallelized gene prediction based on Prodigal. This is just a small wrapper around the prodigal gene prediction program that splits input into chunks and processes them im parallel, since prodigal does not support multithreading by itself. The wrapper supports all command line parameters ...
BRAKER3 is the latest pipeline in the BRAKER suite. It enables the usage of RNA-seqandprotein data in a fully automated pipeline to train and predict highly reliable genes with GeneMark-ETP and AUGUSTUS. The result of the pipeline is the combined gene set of both gene prediction tools, whic...
Graph neural networks (GNNs) and similar algorithms were implemented using Google Colab and Python. Cytoscape and CytoHubba are open-source software platforms used for network analysis and visualization. GNNswer...
To ensure the training data and the RNA-seq samples for prediction shared the same genes and feature scale, first the human gene symbols were converted to mouse gene symbols (14.603 genes) and then both the training and the RNA-seq datasets were pre-processed with Scaden process. The two ...
Gene expression data (RNA/DNA microarray) are often used to develop such prediction models. Results The outcome of the present work is an experimental methodology to develop prediction models, based on robust gene signatures, for the classification of cigarette smoke exposure and cessation in humans...
Graph Attention Network-Based Prediction of Drug-Gene Interactions of Signal Transducer and Activator of Transcription (STAT) Receptor in Periodontal Regeneration doi:10.7759/cureus.68764IntroductionThe signal transducer and activator of transcriptio...