45 results about "Pathway analysis" patented technology

The invention discloses a method for screening and annotating of longissimus dorsi differential expression genes of pigs of different varieties. The method comprises the following steps that 1, sampling and sequencing are conducted; 2, original data are processed; 3, differential genes are screened; 4, function significance enrichment analysis is conducted; 5, Pathway significance enrichment analysis is conducted. According to the method, a high throughout transcriptome sequencing technology is adopted, the gene expression profiles of longissimus dorsi tissue of the pigs of different varieties are established, the differential expression genes are obtained, the differential expression genes are selected through GO analysis and pathway analysis, the key gene of controlling the meat quality trait is determined, control over muscle growth and development and fat metabolism can be better understood, and the molecular biology evidence is provided for the following research of the molecular mechanism forming the difference of the meat quality and the growth trait of domestic and oversea varieties.

The invention relates to biological feed, in particular to a biological fermented feed and a preparation method thereof. The method consists of: subjecting Aspergillus niger, Bacillus licheniformis, Bacillus coagulans, Bacillus subtilis, Lactobacillus plantarum, and Candida utilis respectively to two-stage liquid fermentation culture, and then conducting three-stage solid fermentation culture to obtain fermented culture, i.e. biological feed. The fermented culture provided by the invention utilizes neural network, pattern recognition, genetic algorithm and other optimization methods to optimize the fermentation conditions, a biosynthesis network is constructed according to the principle of metabolic engineering, and pathway analysis and metabolic flux control are carried out on the synthetic network on the basis, and enzymolysis, anaerobism, aerobiosis, bacterium cultivation and other processes are employed, thus increasing the protein content, reducing the content of crude fiber, improving the palatability and fragrance, increasing probiotics, and removing toxins from feed raw materials.

The invention belongs to the technical field of tumor diagnosis, and particularly relates to identification of esophageal cancer related characteristic pathways of and a construction method of an early diagnosis model. The identification and constructing method includes the steps: expression spectrum preprocessing, differential expression gene extraction, sample cluster analysis, gene cluster analysis, specific gene set functional pathway analysis, comparison of pathway aberration scores, comparative analysis of functional differences, construction of esophageal cancer specific co-expression networks, characteristic selection of genes, prediction of deep learning models, and the like. The method of the invention divides genes into different groups according to expression similarity and functional consistency of the genes, and analyzes the genes in the form of gene collection, thus being able to avoid the disadvantages of high false positive rate, big random error and unstable result inthe traditional method, and also being able to more specifically identify the function significantly associated with esophageal cancer.

The invention discloses a non-parametric miRNA data analysis method based on a miRBase database. The non-parametric miRNA data analysis method includes the following steps: a file preparation step; alogout data filtering step; a sRNA classified annotation step; a miRNA differential analysis step; a miRNA function and pathway analysis step; a miRNA sequence feature analysis step; and a result arrangement step. The non-parametric miRNA data analysis method based on a miRBase database has the advantages of performing analysis of miRNA sequencing data for reference-free miRNA sequences without the species; being comprehensive in the results including the miRNA analysis content involved and other measured small RNA information annotations; automatically arranging all the analysis results, andafter completing the analysis of each part, automatically counting the results, being visualized, and performing sorting and arrangement to enable the results to be arranged at a glance and used directly for report generation; and being visible for all the steps and being easy to query the errors.

Global transcriptional profiling of CTLs in tumors and adjacent non-tumor tissue from treatment-naive patients with early stage lung cancer revealed molecular features associated with robustness of anti-tumor immune responses. Major differences in the transcriptional program of tumor-infiltrating CTLs were observed that are shared across tumor subtypes. Pathway analysis revealed enrichment of genes in cell cycle, T cell receptor (TCR) activation and co-stimulation pathways, indicating tumor-driven expansion of presumed tumor antigen-specific CTLs. Marked heterogeneity in the expression of molecules associated with TCR activation and immune checkpoints such as 4-1BB, PD1, TIM3, was also observed and their expression was positively correlated with the density of tumor-infiltrating CTLs. Transcripts linked to tissue-resident memory cells (TRM), such as CD 103, were enriched in tumors containing a high density of CTLs, and CTLs from CD 103^high tumors displayed features of enhanced cytotoxicity, implying better anti-tumor activity. In an independent cohort of 689 lung cancer patients, patients with CD103^high (TRM rich) tumors survived significantly longer. In summary, the molecular fingerprint of tumor-infiltrating CTLs at the site of primary tumor was defined and a number of novel targets identified that appear to be important in modulating the magnitude and specificity of anti-tumor immune responses in lung cancer.

The invention provides a GC-MS (Gas Chromatography-Mass Spectrometer) combined technology-based metabonomics research method for resistance of an asarum and red peony root composition to a cerebral ischemia-reperfusion injury. The method is realized through the following steps: (1) detecting and analyzing a serum sample and a urine sample of a mouse by adopting a GC-MS combined technology; (2) analyzing data by using PCA (Primary Component Analysis) and PLS-DA (Partial Least Square)-DA (Discriminant Analysis),and performing metabolite identification in combination with SPSS17.0 by using an NIST (National Institute of Standards and Technology) database to find out a final differential metabolite; (3) performing pathway analysis on the differential metabolite through MetPA online analysis software. According to the method, by analysis of the serum sample and the urine sample of the mouse through the GC-MS combined technology, respective identification of the differential metabolites of the serum sample and the urine sample of the mouse, and metabolic pathway analysis of the differential metabolites, the action mechanism of the asarum and red peony root composition resisting the cerebral ischemia-reperfusion injury can be comprehensively evaluated from the overall level, so that a demonstrative research is provided for explanation of the metabonomics and the action mechanism of a traditional Chinese medicine composition.

The present inventive subject matter provides apparatus, systems, and methods in which a diagnostic test is identified, where the diagnostic test is for determining whether a particular treatment is effective for a particular patient based on one or more characteristics of a patient's cells. When a treatment is developed with the potential to treat one or more diseases, the drug can have different effects on different cell lines related to the diseases. A machine learning system is programmed to infer a measurable cell characteristic, out of many different measurable cell characteristics, that has a desirable correlation with the sensitivity data of different cell lines to a treatment. The machine learning system is programmed to then determine, based on the correlation, a threshold level of the cell characteristic the patient should exhibit in order to recommend administering the treatment.

System, method and computer product for predicting biological pathways. In this disclosure, a data extraction module automatically extracts biological data from biological data sources. A pathway database contains the extracted biological data. A pathway analysis module assimilates the biological data into a hypotheses prediction for generating a pathway. A visualization module generates a visual representation of the pathway generated by the pathway analysis module.

The invention relates to a mass spectrum data missing value filling method and system based on non-negative matrix factorization, and the method comprises the steps: carrying out the pre-filling of missing values of a data set matrix, and obtaining a missing-free initial data matrix; carrying out logarithm transformation on all elements in the initial data matrix without loss; taking a group of dimension parameters of non-negative matrix factorization, and respectively carrying out non-negative matrix factorization to obtain a group of corresponding reconstruction matrixes; performing exponential transformation on the element values of the reconstructed matrix; calculating reconstruction errors between all reconstruction matrixes after exponential transformation and the missing-free initial data matrix; calculating corresponding weights under different reconstruction matrixes according to the reconstruction errors; performing weighted average on the reconstruction matrix to obtain a weighted reconstruction matrix; filling the missing positions in the data set matrix with the element values at the corresponding positions in the weighted reconstruction matrix; and carrying out characteristic metabolite identification and pathway analysis based on the missing-free final data matrix. According to the method, the data filling precision can be improved.

About 70% to 80% of breast cancers express estrogen receptor-α (ERα), and estrogens play important roles in the development and growth of hormone-dependent tumors. Together with lymph node metastasis, tumor size and histological grade, ER status is considered one of the prognostic factors in breast cancer, and an indicator for hormonal treatment. 147 genes and 112 genes with significant P-value and having significant differential expression between ER+ and ER− tumors were identified from the LCM data set and bulk tissue data set, respectively. 61 genes were found to be common in both data sets, while 85 genes were unique to the LCM data set and 51 genes were present only in the bulk tumor data set. Pathway analysis with the 85 genes using Gene Ontology suggested that genes involved in endocytosis, ceramide generation, Ras/ERK/Ark cascade, and JAT-STAT pathway may play roles related to ER. The gene profiling with LCM-captured tumor cells provides a unique approach to characterize and study epithelial tumor cells and to gain an insight into signaling pathways associated with ER.

A method for assigning ranking scores to pathways in a set of pathways for classifying patients is disclosed. The method comprises the steps of comparing biomolecular datasets from different groups of patients and performing an analysis in order to assign ranking scores to pathways in a set of pathways. Furthermore, a method for using cancer pathway evaluation to support clinical decision making is disclosed. This assessment is further used for stratifying ovarian cancer patients based on chemosensitivity to platinum based drugs, the standard chemotherapy. We present the method for evaluation and ranking of the most relevant pathways responsible for platinum sensitivity. Clinical decision support software system should be able to then visualize this information for a clinician, contextualize it within a patient data set and help make a final decision on the potential responsiveness.

The present disclosure provides for rapid identification of mechanism of action (MOA) for drugs and toxins, and does so in a rapid (30 days or less) fashion. The methods use a combination of high throughput bioinformatics and pathway analysis that examine a wide variety of biological parametics.

The invention relates to an enzyme for catalyzing hydroxylation of an abietane type tricyclic diterpenoid compound C-14, the enzyme is tripterygium wilfordii cytochrome p450 oxidase CYP82D274, and the invention also relates to polynucleotide CYP82D274 for coding the enzyme, and the polynucleotide CYP82D274 is used for catalyzing hydroxylation of the abietane type tricyclic diterpenoid compound C-14. An enzyme catalysis experiment proves that the triptolide gene has the function of catalyzing hydroxylation of triptolide biosynthesis intermediates, namely miltidiene, dehydroabietic acid and triptobenzene terpene D. The triptolide gene has the advantages that triptolide biosynthesis pathway analysis is further promoted, an important gene element is provided for synthesis biological production of the triptolide intermediates, and the triptolide gene has a wide application prospect. The method has important significance on synthesis regulation and control of abietane type tricyclic diterpenoid compounds such as triptolide and the like.