Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Age prediction method based on ensemble learning of intestinal flora prediction model

A technology of gut flora and prediction method, applied in the intersection of microbiology and computer science, can solve the problems of host background factors, single model algorithm, redundant features, etc., to achieve anti-aging intervention, reduce prediction bias, The effect of improving accuracy

Pending Publication Date: 2022-02-25
JIANGNAN UNIV
View PDF0 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to solve the problems of low accuracy, low data utilization rate, redundant features, single model algorithm and influence by host background factors in the current age prediction model and prediction method based on intestinal flora. An adult age prediction method based on integrated learning of intestinal flora prediction model and its application

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Age prediction method based on ensemble learning of intestinal flora prediction model
  • Age prediction method based on ensemble learning of intestinal flora prediction model
  • Age prediction method based on ensemble learning of intestinal flora prediction model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0065] This embodiment provides an age prediction method based on integrated learning of the intestinal flora prediction model, combining figure 1 Shown, described age prediction method comprises the steps:

[0066] Step 1: Obtain the intestinal flora data samples of adults of different ages as the original data, and collect the background information of the host corresponding to the data samples, including age and geographical characteristics;

[0067] Step 2: Preprocessing the acquired raw data, the preprocessing includes sorting out the background information of the host and quality control of the raw data, annotation of the composition and relative abundance of intestinal flora species and metabolic pathways, where the relative abundance Degree refers to the relative abundance of gut flora species and metabolic pathways;

[0068] Step 3: Normalize the annotated intestinal flora species and relative abundance information tables of metabolic pathways, and select the best al...

Embodiment 2

[0110] According to this embodiment, the age prediction method based on the integrated learning of the intestinal flora model of the present invention, the specific implementation steps are as follows:

[0111] (1) Raw data obtained from gene databases such as NCBI (National Center for Biotechnology Information) and EMBL (European Molecular Biology Laboratory) were preprocessed, including host background information sorting and quality control of raw data, species and Annotation of composition and abundance of metabolic pathways.

[0112]For the sample background information collected, according to the United Nations subregions, standard country or area codes (United Nations subregions, standard country or area codes for statistical use), the geographical location of the geographical factor is used to cluster from the country level to the subinterval level.

[0113] For the obtained original data of intestinal flora, the sample sequence was compared with the human genome seque...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an age prediction method based on ensemble learning of an intestinal flora prediction model, which comprises the following steps: acquiring original data of human intestinal flora metagenomics, performing quality control on the acquired genome data, acquiring an abundance table of intestinal flora species composition and metabolic pathway composition, and constructing a sample data set; performing feature selection on the sample data set; constructing a multi-class age prediction model by using the screened features in combination with host regional information, determining hyper-parameters which enable the prediction model to be higher in precision by using grid search, and training and predicting each optimal prediction model to obtain an integrated age prediction method; and finally, predicting the age of the sample by using the determined intestinal flora characteristics and an integrated age prediction method, and determining age-related key species and pathways through characteristic interpretation. According to the invention, an integrated learning method is adopted, so that the age prediction accuracy is effectively improved; the regulation of intestinal flora can be directionally guided, so that anti-aging intervention is realized.

Description

technical field [0001] The invention relates to an age prediction method based on integrated learning of an intestinal flora prediction model, which belongs to the cross technical field of microbiology and computer science. In particular, the present invention relates to an adult age prediction method based on integrated learning of intestinal flora prediction model. Background technique [0002] Human aging is a continuous process, which will lead to the reduction of the physiological function of the body organs, and then lead to the occurrence of diseases. With the development of intestinal flora sequencing projects such as the Human Microbiome Project, the understanding of the interaction between intestinal flora and host organisms continues to deepen. Studies have shown that the composition, function and metabolites of the intestinal flora will continue to change with age, and the age-specific changes in the intestinal flora will further affect the intestinal nutritiona...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G16H50/30G16H10/60G16H50/50
CPCG16H50/30G16H10/60G16H50/50
Inventor 王鸿超陈宇涛陆文伟朱金林赵建新张灏陈卫
Owner JIANGNAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products