244 results about "Methylation Site" patented technology

The invention provides a protein methylation site prediction method fusing quantum and region perception, which comprises the following steps: step 1, acquiring a protein sequence as a data source, and respectively constructing a training set and an independent test set; 2, constructing a multi-modal feature for each protein sequence by adopting a three-way nested scattering network, and fusing the multi-modal features to obtain an optimized fusion feature tensor; and step 3, inputting the optimized fusion feature tensor into a RaQMeNet network model, and performing a methylation site prediction task. The performance indexes of the method are greatly superior to those of the prior art, and the method has higher adaptability, stability and interpretability, can be widely applied to a plurality of bioinformatics and biological medicine related fields such as protein function annotation, disease mechanism research and drug target discovery, and has good application prospects and commercial values.

The invention relates to a DNA methylation detection method and device and electronic equipment, and the method comprises the following steps: obtaining a DNA sequence to be detected; obtaining original electric signal data and a base sequence corresponding to the DNA sequence to be detected through a nanopore sequencing technology; obtaining a methylation detection result corresponding to the DNA sequence to be detected according to the original electric signal data, the base sequence and a deep learning model; wherein the deep learning model comprises a sequence feature extraction module, a signal feature extraction module, a feature fusion module and a classification module; the sequence feature extraction module comprises a Transform encoder; the signal feature extraction module comprises a Conformer encoder; the feature fusion module comprises a Transform decoder; the classification module comprises a full connection layer; according to the method provided by the invention, the identification accuracy of the methylation site can be improved, high-precision methylation detection is realized, and the problems of gradient disappearance and gradient explosion can be effectively relieved.

The invention discloses a method for male biological age assessment and aging prediction based on DNA methylation data of peripheral blood. The method comprises the following steps: screening out DNA methylation sites related to male biological age and senescence by retrieving related literatures and research results; downloading DNA methylation chip sequencing data, and screening out male data; screening the modeling database and the DNA methylation sites to obtain a modeling sample and modeling sites; establishing an epigenetic clock model; comparing the epigenetic clock model with a traditional model, and performing model evaluation; carrying out biological age evaluation and aging prediction; according to the method, the regression models are established according to three methods based on screening of global male samples, few loci with top correlation ranking are selected from the regression models, few locus models are re-established to evaluate the age and the aging degree of people, and the method has the advantages of accurate male sample positioning, low prediction cost and convenience in later product popularization.

The invention relates to the technical field of gene detection, in particular to application of a DNA methylation site in diagnosis of type 2 diabetes mellitus, a kit and a method thereof. Clinical detection proves that the methylation site cg06087988 has significant difference between a type 2 diabetes mellitus patient and a non-type 2 diabetes mellitus individual, and can act on diagnosis / prediction of type 2 diabetes mellitus.

The invention discloses a DNA methylation biomarker combination for prostate cancer detection and application of the DNA methylation biomarker combination, and belongs to the technical field of biological medicine. The DNA methylation biomarker combination comprises a combination of methylation sites indicated by CG in the SEQ ID NO: 1 sequence of the USP44 gene and the SEQ ID NO: 2 sequence of the HIF3A gene. It is reported for the first time that the methylation levels of the USP44 gene and the HIF3A gene are detected at the same time to conduct auxiliary diagnosis on the prostatic cancer, a sample urine detection result shows that the sensitivity is 97.14%, the specificity is 97.78%, and the non-invasive and reliable prostatic cancer detection method is provided and has good application prospects in early screening of the prostatic cancer.

The invention relates to the technical field of cancer risk prediction, in particular to a deep learning cancer risk prediction method and system based on a methylation sequence. The method comprises the following steps: acquiring DNA methylation sequencing data and reference genome annotation data in a blood sample of a cancer patient; performing functional region classification processing on the DNA methylation sequencing data according to the reference genome annotation data to obtain promoter subregion methylation data, enhancement subregion methylation data and transcription factor binding site methylation data; performing dynamic sequence similarity calculation processing on the methylation data of the promoter region to obtain a first feature vector containing importance weight of the promoter region of the cancer-related gene; the methylation sites are classified according to the functions of the methylation sites in the transcriptional regulation pathway, so that the biological interpretation of the characteristics is improved, and the synergistic effect among different functional regions can be captured.

The invention discloses a method for predicting an RNA (Ribonucleic Acid) methylation site, which is based on a multi-modal feature fusion and semantic vector embedding technology and is used for remarkably improving the recognition precision of an m7G modification site. The method comprises the following steps: firstly, constructing an RNA sequence data set containing positive and negative samples, and dividing the RNA sequence data set into a training set and an independent test set according to a predetermined proportion; then, multi-modal features are extracted through One-hot coding (One-hot), nucleotide chemical property coding (NCP), electron-ion interaction potential coding (EIIP) and local nucleotide composition coding (ENAC), and context semantic information of a nucleotide sequence is obtained in combination with a DNA2Vec model; according to the model, a multi-modal feature fusion path (MRF) and a DNA2Vec embedding path are adopted, after feature dimension compression is carried out through a full connection layer, a Transform encoder is used for capturing a long-range dependency relationship, and a prediction probability is calculated through a Sigmoid activation function. In the optimization process, batch normalization, Dropout and Adam optimizers are adopted, and the binary cross entropy loss function is minimized. Finally, the performance of the model is evaluated through five-fold cross validation, and the generalization ability of the model is verified on an independent test set. According to the method, through multi-source feature fusion and hierarchical modeling, the analysis capability of sequence information is remarkably improved, and an accurate calculation tool is provided for RNA modification prediction.

The invention discloses application of a Lys35 site of a PC4 protein as a target spot in preparation of tumor diagnosis and treatment products. The invention provides application of a Lys35 site of a PC4 protein as a target spot in preparation of a tumor diagnosis product. The research shows that the Lys35 site methylation of the PC4 protein can promote the cell cycle progress of tumor cells and promote the proliferation growth and malignant progression of the tumor cells, and the scheme for inhibiting the site methylation can be used for developing tumor treatment drugs. Therefore, the Lys35 site of the PC4 protein can be used as a key target to be applied to development of tumor diagnosis products and targeted therapy drugs. The invention further develops the PC4 protein Lys35 methylation antigen peptide and the antibody capable of specifically recognizing the PC4 protein Lys35 methylation site, and the PC4 protein Lys35 methylation antigen peptide and the antibody can be applied to regulation and control of tumor cell proliferation or growth, can be used for developing diagnostic products and targeted therapy drugs for clinical tumor diseases, and have good clinical application value.

The invention discloses a Nur77 methylation site mutation peptide based on structural modification design and application of the Nur77 methylation site mutation peptide in promoting embryo implantation, according to the mutation peptide, arginine at the 346th site of Nur77 is mutated into lysine, and methylation modification of Nur77 is reserved while phosphorylation of Nur77 is inhibited, so that the transcriptional activity of Nur77 is enhanced. It is found that the mutant peptide can promote deciduation of endometrial interstitial cells, remarkably improve deciduation disorder of infertility mice in in-vivo experiments and improve the embryo planting rate of low-fertility mice. Therefore, the mutant peptide is expected to become a new medicine for treating the uterine-derived infertility and has important clinical application value. The invention also relates to a preparation method of the mutant peptide and application of the mutant peptide in a pharmaceutical composition and a treatment method.

The invention relates to the technical field of biology, in particular to an MSRE-RPA-CRISPR / Cas12a detection system aiming at a breast cancer methylation site and application of the MSRE-RPA-CRISPR / Cas12a detection system. The MSRE-RPA-CRISPR / Cas12a systems of the four breast cancer methylation sites are constructed and optimized, the visual detection method for the breast cancer methylation sites based on the MSRE-RPA-CRISPR / Cas12a systems is established, the detection method has the advantages of being high in sensitivity, high in specificity and short in detection time, does not depend on large-scale instruments and equipment, the result is visual and visual, and the method is suitable for large-scale popularization and application. The method is suitable for point-of-care testing (POCT).

The invention discloses a model training method and device and a DNA methylation recognition method. The model training method comprises the following steps: performing digital coding processing on DNA methylation site data to obtain a first feature vector; capturing a dependency relationship inside the first feature vector by adopting a self-attention layer to obtain a second feature vector; performing parallel convolution processing on the second feature vector to obtain a plurality of convolution features of different scales; performing weighted aggregation on each convolution feature according to the importance weight to obtain a plurality of third feature vectors; performing fusion processing on the plurality of third feature vectors to obtain a classification result; and determining a loss function according to a classification result, and obtaining a trained deep learning model under the condition that the loss function meets a preset convergence condition. According to the method and the device, the technical problem that the generalization ability of the model is limited due to the fact that the dependency of the related model for identifying the DNA methylation site on feature coding is high is solved.

The development of a methylation capture panel that targets methylation sites that vary between tissues at high sequencing depth means that the projected cost for a sample run on the proposed capture technology is 10-fold smaller than with whole genome bisulfite sequencing (WGBS). This unexpected combination of methylation sequencing, cell type identification, machine learning, and capture technology enables a previously unattainable ability to predict disease status. These methods can be used to diagnose, prognose, and stage disease conditions including amyotrophic lateral sclerosis (ALS) and other degenerative conditions. In addition, it offers great advantages for other cfDNA-based detection applications, such as cancer and pregnancy-related conditions.

The present invention discloses an in vitro method for obtaining DNA methylation biomarkers as exquisite DNA methylation positions in the human genome (i.e., CGIDs) that predict cervical cancer especially at as yet inaccessible early stages by examining progression of “categorical” DNA methylation alterations in three stages of premalignant lesions (cervical intraepithelial neoplasia (CIN)), progressing from CIN1 to CIN3. The present invention discloses combinations of CGIDs for detecting with high specificity and sensitivity cervical cancer by measuring their DNA methylation status and deriving a “methylation score”, which is useful as a biomarker for cervical cancer. Also disclosed are kits for predicting cervical cancer using such CGIDs using multiplexed next generation sequencing methylation assays, pyrosequencing assays and methylation specific PCR. The DNA methylation markers (CGIDs) described in the present invention are useful for cervical screening and early detection of cervical cancer by any person skilled in the art to detect cervical cancer.

The present invention provides an in vitro method for determining the X chromosome reactivation (X-Ra) level of a female subject, the method comprising the steps of (a) determining the methylation status of at least 10 CpG sites of Table 1 in a DNA-containing sample from the female subject; and (b) calculating the fraction of the CpG sites analyzed in step (a) that are hypomethylated. The invention also provides in vitro methods for determining the biological age of a female subject, diagnosis and / or prognosis of an age-related disease or disorder or an infection, and for determining the gestational age of a fetus.

The present invention relates to the field of gene detection, and particularly to a primer-probe combination, a kit and their applications for detecting the benign and malignant nature of pulmonary nodules. The primer-probe combination includes primer pairs and probes for detecting gene mutation sites and methylation sites, and can achieve simultaneous detection covering the EGFR L858R mutation site, the EGFR 19Del mutation site, and the methylation sites of the HOXA7, CCNA1, and ZNF808 genes at one time. Thus, the present invention is a simple, rapid and accurate combined detection scheme for DNA methylation and gene mutation to assist in differentiating the benign and malignant nature of pulmonary nodules; at the same time, the primer-probe combination can achieve rapid pre-cancer screening, and also has application values such as accurate medication guidance and prognosis and metastasis risk prediction.

A method and device for predicting the bull semen quality. The method comprises: on the basis of the variation of methylation level values, using known methylation spectrum data of methylation sites of a bull sperm to select 83 methylation sites; on the basis of an elastic net regression algorithm, using the selected methylation sites to construct an epigenetic clock; and using the epigenetic clock to predict the age of a bull to be detected. The age of a bull can be predicted on the basis of an epigenetic clock, and the bull semen quality can be predicted on the basis of an epigenetic acceleration. The present invention can be applied to bull variety breeding and bull breeding.

The invention discloses a biological sample processing method and device, equipment and a storage medium, and belongs to the technical field of data processing. The method comprises the following steps: performing methylation sequencing on nucleic acid of a biological sample to obtain state information of methylation sites in a genome of the nucleic acid; on the basis of the state information of the methylation sites, obtaining characterization characteristics of the methylation sites; extracting characterization characteristics of the biological sample based on the characterization characteristics of the methylation sites; and performing cancer recognition on the biological sample based on the characterization characteristics of the biological sample to obtain a cancer recognition result of the biological sample. According to the method, the device, the equipment and the medium, the state information of the methylation site can reflect the characteristics of the nucleic acid of the biological sample to a large extent, the characterization characteristics of the biological sample are obtained by considering the characteristics of the nucleic acid of the biological sample, the biological sample can be more reliably characterized, cancer recognition is performed on the biological sample based on the characterization characteristics, and the accuracy of cancer recognition is improved. And the accuracy of a cancer identification result of a biological sample is improved.

The invention belongs to the technical field of bioinformatics and deep learning, and particularly relates to a DNA methylation site prediction method, system and device and an electronic medium, and the method comprises the following steps: respectively coding single bases in a DNA sequence into four molecular fingerprints, and constructing each base into a molecular map structure; performing high-order feature extraction on the four molecular fingerprints through a multi-layer perceptron to generate molecular fingerprint features; modeling the molecular graph structure by adopting a multi-head graph attention network, calculating and normalizing attention scores among nodes, carrying out weighted summation on neighbor node features, and carrying out multi-head attention fusion to generate molecular graph features; splicing the molecular fingerprint features and molecular map features, and inputting the spliced molecular fingerprint features and molecular map features into a deep convolution gated channel attention module to generate fused features; and obtaining a prediction probability of the fused features, and judging whether the features are methylation sites or not according to the prediction probability. According to the invention, the identification capability of methylation sites can be improved.

A method for detecting a methylated genomic locus is provided. In certain embodiments, the method comprises: a) treating a nucleic acid sample that contains both unmethylated and methylated copies of a genomic locus with an agent that modifies cytosine to uracil to produce a treated nucleic acid; b) amplifying a product from the treated nucleic acid using a first primer and a second primer, wherein the first primer hybridizes to a site in the locus that contain methylcytosines and the amplifying preferentially amplifies the methylated copies of the genomic locus, to produce an amplified sample; and c) detecting the presence of amplified methylated copies of the genomic locus in the amplified sample using a flap assay that employs an invasive oligonucleotide having a 3′ terminal G or C nucleotide that corresponds to a site of methylation in the genomic locus.

This invention discloses a method for constructing a gene methylation diagnostic model for differentiated thyroid cancer (PTC). The method includes the following steps: S1, obtaining a test sample; S2, extracting and storing DNA from the test sample; S3, performing methylation analysis; S4, establishing a diagnostic model based on DNA methylation, where the model shows that patients with cg03596178, cg06033721, cg06688989, cg07209244, cg07485775, cg14484681, cg19979108, and cg20943461 are more likely to experience disease progression and are considered risk factors; S5, cross-validating and evaluating the performance to obtain the gene methylation diagnostic model. This model, by detecting and statistically analyzing specific methylation sites, can differentiate patients with recurrent or metastatic characteristics in differentiated thyroid cancer. The relevant model can assist in the clinical diagnosis and follow-up of thyroid patients.

The present invention provides a method for determining a mortality risk and / or probability of a healthy lifespan of a dog; said method comprising a) providing a DNA methylation profile from a sample obtained from the dog; and b) determining a mortality risk and / or probability of a healthy lifespan for the dog using the DNA methylation profile; wherein the DNA methylation profile comprises at least one methylation site as listed in Table 1.

The invention relates to the technical field of biological information, in particular to application of a biological factor developed based on MAMMOT in preparation of a kit for sepsis identification. The biological factors comprise a genome and a microbiome; the genome comprises a plurality of genes such as PMS2P4 and the like, and the microbiome comprises a plurality of bacteria such as Citrobacter werkmanii, Streptococcus oranis and the like, and a plurality of bacteriophages such as Escherichia virus Lambda, Campylobacter phage A11a and the like. The invention further discloses a preparation method of the microbiome. A plurality of sepsis-related cfDNA host methylation sites and a plurality of sepsis-related bacteria and bacteriophages are excavated for the first time, and the biological factors can be applied to sepsis identification and have important values in the fields of sepsis-related detection and patient death rate prediction.

A method, apparatus, storage medium, and program product for tracing the source of disease-affected tissues or organs, the tracing method comprising: acquiring methylation data of multiple tissues or organs, wherein the methylation data of the tissues or organs are methylation data of healthy tissues or organs; establishing an average methylation rate matrix based on the methylation data of multiple tissues or organs, wherein the average methylation rate matrix includes the average methylation rate of each tissue or organ at multiple methylation sites or methylation regions; determining specific methylation sites or specific methylation regions based on the average methylation rate matrix; acquiring methylation data of a sample to be traced; and performing tracing based on the average methylation rate of multiple tissues or organs at the specific methylation sites or specific methylation regions and the methylation data of the sample to be traced.

The invention provides a DNA methylation biomarker for liver cancer detection and application of the DNA methylation biomarker, and belongs to the technical field of biology. The biomarker disclosed by the invention is selected from any one of the following methylation sites: cg13597025, cg00033450, cg20335273, cg06121113, cg27629428, cg02307184, cg15602112 and cg26472334, and the biomarker disclosed by the invention can be used for detecting the methylation sites of the cg13597025 and the cg00033450. The biomarker provided by the invention can be used for noninvasive detection of liver cancer, and has important significance for early screening of liver cancer.

To provide a new method for testing for sensitivity of chemotherapy against colorectal cancer using, as an indicator, a methylation site that has not been conventionally known to be an indicator of responsiveness to chemotherapy of colorectal cancer.SOLUTION: The present invention provides a method for testing for sensitivity of chemotherapy against colorectal cancer, the method using, as an indicator, methylation in at least one site selected from a group consisting of CpG sites comprised in regions (i) to (xvi) in DNA collected from a colorectal cancer patient (the regions (i) to (xvi) are as described herein).SELECTED DRAWING: None

The application belongs to the technical field of molecular biology and medicine, and discloses a methylation marker for detecting the benignity and malignancy of thyroid nodules and an application. 780 new methylation sites are identified, 273 tumor occurrence and development related genes are associated, and the Fc gamma R-mediated phagocytosis signal pathway is involved. The methylation marker for detecting the benignity and malignancy of thyroid nodules comprises multiple genes and multiple methylation sites. The methylation level of multiple genes and multiple sites is detected, the problem of low and unstable methylation signal of single gene or single site is overcome, and thus the sensitivity and specificity of detection are improved.

The present invention relates to a method of authenticating a test animal-derived product sample, the method comprising the steps of: (a) determining a test methylation profile of one or more preselected methylation sites within a genomic material obtained from the test animal-derived product sample; and (b) comparing the test methylation profile obtained from (a) to a reference methylation profile obtained from a control animal having the same biological classification unit as the test animal from which the product sample is derived, wherein the control animal is cultivated under a known special type of animal husbandry; wherein a significant similarity of the test methylation profile of (a) to the reference methylation profile from the control animal indicates that the test animal has been cultivated under the same special type of animal husbandry as the control animal, and the test animal-derived product is so verified; wherein the difference in the test methylation profile of (a) compared to the reference methylation profile of the control animal indicates that the test animal has been cultivated in another special type of animal husbandry compared to the control animal; and wherein the preselected methylation site is a CpG site selected from gene or genomic DNA regions from control and test animals exhibiting the highest degree of methylation variation during method training; and wherein the test methylation profile has a significant similarity to the reference methylation profile when the test methylation profile overlaps the reference methylation profile defined by a plurality of training samples using principal component analysis and / or multi-dimensional scaling analysis; and wherein the methylation profile is determined using at least one method selected from the group consisting of PCR, methylation-specific PCR, real-time methylation-specific PCR, PCR assays using methylated DNA-specific binding proteins, quantitative PCR, DNA chip-based assays, pyrosequencing, bisulfate pyrosequencing, methylated DNA immunoprecipitation sequencing, and combinations thereof; and wherein the test animal is selected from livestock or poultry.

The invention discloses a novel gene participating in a DNA methylation pathway and application of the novel gene in plant epigenetic regulation. Experiments show that a hypermethylation site exists in an arabidopsis thaliana RMU1 gene promoter region, the methylation level of the arabidopsis thaliana RMU1 gene promoter region is obviously reduced under the background of an RdDM defective mutant, the transcriptional level of the arabidopsis thaliana RMU1 gene promoter region is obviously improved, and it is proved that expression of the arabidopsis thaliana RMU1 gene promoter region is regulated by After the RMU1 gene is mutated, the methylation level of the whole gene is obviously changed, the methylation levels of CHG and CHH sites of the rmu1 mutant in gene upstream and downstream 2kb regions, transposon upstream and downstream 2kb regions and transposon body regions are obviously higher than those of wild arabidopsis thaliana, and the phenomenon is not observed in a gene body region, so that the RMU1 participates in regulating and controlling the DNA methylation level. The arabidopsis thaliana RMU1 gene has important effects and application prospects in epigenetic editing tool development, epigenetic breeding and transposon domestication.

The invention relates to the technical field of colorectal cancer auxiliary detection, and particularly discloses a blood methylation site combination and a detection kit for early diagnosis of colorectal cancer, and the method comprises the following steps: providing a blood sample of a person to be detected for obtaining cfDNA; the cfDNA is subjected to bisulfite treatment, and the transformed DNA is obtained; amplifying the transformed DNA by using a multiplex fluorescence PCR (Polymerase Chain Reaction) method to obtain fluorescence signal data of each gene; calculating a Ct value of each gene based on the fluorescence signal data, comparing the Ct value with a preset Cut-off value, and judging whether the colorectal cancer exists or not; according to the present invention, the invasive operation of the colonoscope can be replaced, the screening can be completed through the blood sample, the patient compliance can be significantly improved, the method is suitable for the large-scale early screening, the trace tumor signal in the blood can be efficiently captured based on the methylation marker highly related to the colorectal cancer, and the accurate early canceration identification can be achieved.

The invention relates to a tumor-related DNA methylation marker combination, which is selected from at least one of the following: a target sequence as shown in SEQ ID NO: 1-SEQ ID NO: 10, a nucleic acid fragment with the length of at least 15 oligonucleotides or a complementary nucleic acid fragment thereof, and the nucleic acid fragment comprises at least one methylation site indicated by CG. The invention also relates to a detection kit for the methylation marker combination. According to the invention, the combination of the co-methylation states of a plurality of specific methylation regions is used for distinguishing and analyzing the occurrence of tumors, especially kidney cancer, the specific methylation combination has high sensitivity for distinguishing the occurrence of kidney cancer, and the detection method is simple, convenient and feasible. The primer pair combination of the kit overcomes the defect of false positive caused by detection mismatch of a single methylation site in the aspect of primer sequence design, and the interaction between a plurality of methylation biomarker primers and probe pair combinations is considered.