59 results about "Gene Annotation" patented technology

A computational systems pharmacology framework consisting of statistical modeling and machine learning based on comprehensive integration of systems biology data, including drug target data, protein-protein interaction (PPI) networks, and gene ontology (GO) annotations, and reported drug side effects, can predict drug toxicity or drug adverse reactions (ADRs). Biomolecular network and gene annotation information can significantly improve the predictive accuracy of ADR of drugs under development. The use of PPI networks can increase prediction specificity, and the use of GO annotations can increase prediction sensitivity.

The invention discloses a gene annotation method and a gene annotation system. The method comprises the following steps of: obtaining the positions of latent genes on a target genome by a gene prediction method based on sequence characteristics and a statistical model; comparing a known gene sequence and an interspecies homologous conserved sequence with the target genome by a sequence similarity-based gene annotation method and marking the positions of similar genes on the target genome; and integrating and screening prediction results by a weighted voting method according to the positions of the latent genes and the similar genes on the target genome to obtain a comprehensive gene prediction result and corresponding coding sequences. The multi-evidence combined gene annotation method and the system effectively integrate the advantages of the conventional gene annotation method. Transcriptome sequencing data derived from a target species is further utilized, so that the accuracy of agene structure can be ensured and the annotation of the alternative splicing form of the gene can be obtained to the greatest extent at the same time.

The invention belongs to the technical field of bioinformatics, and relates to a method for identifying esophageal squamous cell carcinoma markers on the basis of network index difference analysis. The method comprises the following steps of processing esophageal squamous cell carcinoma gene sample data and normal gene sample data to construct an esophageal squamous cell carcinoma gene interactionnetwork and a normal gene interaction network; using a network module identification method to find out key community structures in the two networks, and performing gene function enrichment analysison the key community structures; extracting same nodes from the two networks, and retaining nodes linked to the same nodes to obtain the two simplified networks; using a global index and a local modular index, analyzing the two simplified networks to obtain genes related to esophageal squamous cell carcinoma; combining a gene function enrichment analysis result with gene annotations and functionalreferences to finally determine candidate markers for diagnosis of esophageal squamous cell carcinoma. A method for studying the esophageal squamous cell carcinoma markers on the basis of gene network difference analysis is further perfected.

The invention relates to a CRISPR-Cas9 system sgRNA action target screening method. The method comprises the steps of (1) obtaining segments with 5'-Nx-NGG-3' sequences (x is an integer ranging from 19 to 22 and N represents A / T / C / G) in genomes by utilizing whole genome sequences and gene annotation information of published species to serve as candidate targets of CRISPR-Cas9 system sgRNA; (2) fragmenting the genomes into fragments of 22-25bp and screening sequences ending with NGG and non-repeated on the genomes; and (3) comparing the sequences of the candidate targets in the step (1) with the screened sequences in the step (2), and performing screening and sorting on corresponding optimal sequences according to mismatch information and a selection formula to obtain an optimal genome sgRNA action target set. The invention furthermore provides an apparatus used for realizing the screening method. The method is suitable for all species with known genomes and gene annotation information, and a universal sgRNA sequence set of whole genome level of the species is quickly and efficiently obtained to build a gene knockout mutant library or a gene knockout animal model.