Viewing and comparing gene neighborhoods is a common step in comparative genomics and gene analysis. We present, “Gene Graphics”, an application that allows for consistent, visually appealing representations of physical gene neighborhoods with minimal effort or expertise.

2025年3月16日 · Tools to curate, browse, search, visualize and download both the ontology and annotations. Includes bioinformatic guides (Notebooks) and simple API access to integrate the GO into your research.

2020年12月10日 · The availability of high-throughput spatial expression data opens the door to methods that can infer such interactions both within and between cells. To achieve this, we developed Graph Convolutional Neural networks for Genes (GCNG). GCNG encodes the spatial information as a graph and combines it with expression data using supervised training.

2022年11月1日 · Genomic Knowledgebase (GenomicKB) is a graph database for researchers to explore and investigate human genome, epigenome, transcriptome, and 4D nucleome with simple and efficient queries.

Mouse over or click genes or lines for details. Dashed lines indicate interactions without text mining support. Click any gene to make it the new center. Click any line to show details about …

2024年7月23日 · We developed pangene, a computational tool to identify gene orientation, gene order, and gene copy-number changes in a collection of genomes. Pangene aligns a set of input protein sequences to the genomes, resolves redundancies between protein sequences and constructs a gene graph with each genome represented as a walk in the graph.

2018年12月7日 · GOnet specifically aims to construct and display interactive graphs that include GO terms and genes while retaining term-gene relationships. Interactivity of a graph gives easy access to node and edge data linking the entries to external databases.

2021年12月1日 · Here, we propose a new multimodal method — AutoGGN — to integrate multi-omics data with molecular interaction networks based on graph convolutional neural networks (GCNs). We evaluated AutoGGN using three classification tasks: single-cell embryonic developmental stage classification, pan-cancer type classification, and breast cancer subtyping.

2019年2月8日 · A gene graph can be defined as a graph-based data structure that describes the order of genes in a genome. The gene graph is an ordered pair G = (V,E) with the vertex set V representing the genes and the edge set E representing …

2025年1月3日 · In this study, we propose to tackle the gene function prediction problem by exploring Gene Ontology graph and annotation with BERT (GoBERT) to decipher the underlying relationships among gene functions. Our proposed novel function prediction task utilizes existing functions as inputs and generalizes the function prediction to gene and gene ...