CN114121166B - Cognitive behavior and molecular network mechanism correlation method based on complex network - Google Patents
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Abstract
The invention provides a method for associating cognitive behaviors with a human molecular network based on a complex network. The method comprises the following steps: constructing a molecular network related to perception and cognitive behavioral phenotypes; constructing a molecular network related to nerves, immunity, endocrine and microecology; and respectively evaluating the association of the perception cognition related phenotype with the molecular network on the whole protein interaction network based on the constructed molecular network by utilizing the average shortest path length of the network and the network association index. According to the invention, through constructing a molecular network related to the cognitive behavioral phenotype, a molecular network related to the nerve, immunity, endocrine and microecological system is constructed, the correlation between the cognitive behavior and the molecular network of the nerve, immunity, endocrine and microecological system can be effectively evaluated, and a database of the molecular correlation mechanism is constructed.
Description
Technical Field
The invention relates to the technical field of sensing and cognitive behaviors, in particular to a method for associating sensing and cognitive behaviors with a molecular network mechanism based on a complex network.
Background
The perception and cognitive behaviors emphasize the occurrence of cognitive activities in psychological or behavioral problems. Cognition generally refers to the process of cognitive activity or cognition, i.e., the process of information processing by individuals of sensory signal reception, detection, conversion, conciseness, synthesis, encoding, storage, extraction, reconstruction, concept formation, judgment, and problem solving. The perception and the cognitive behaviors and the human nerves, immunity, endocrine and micro-ecological systems have close relations, however, the association mechanism between the perception and the cognitive behaviors and the human nerves, immunity, endocrine and micro-ecological systems is still unclear at present, and a necessary technical approach and a molecular association database are still lacked to provide a basis for the research.
Perception and cognitive behaviors are closely related to human nerves, immunity, endocrine and micro-ecological systems, however, because the prior art lacks necessary basic data and effective technical paths and lacks a method path for constructing a molecular network and a molecular database related to the perception and cognitive behaviors, nerves, immunity, endocrine and micro-ecological systems, the association mechanism between the perception and cognitive behaviors and the human nerves, immunity, endocrine and micro-ecological systems is still unclear, and how to evaluate the correlation of the perception and cognitive behaviors with the molecular network of the nerves, immunity, endocrine and micro-ecological systems is unclear.
Disclosure of Invention
The embodiment of the invention provides a method for correlating cognitive behaviors with a human body molecular network based on a complex network, so as to effectively evaluate the correlation of the cognitive behaviors with the molecular network of a nerve, an immunity, an endocrine and a microecological system.
In order to achieve the above purpose, the present invention adopts the following technical scheme.
A method for correlating cognitive behaviors with a human molecular network based on a complex network, comprising:
constructing a molecular network related to perception and cognitive behavioral phenotypes;
constructing a molecular network related to nerves, immunity, endocrine and microecology;
Based on the constructed molecular network, the correlation between the perception cognition related phenotype and the molecular network on the whole protein interaction network is respectively evaluated by utilizing the average shortest path length of the network and the network correlation index, so that a molecular network database is constructed.
Preferably, the construction of the molecular network for perceiving the relation with the cognitive behavioral phenotype comprises the following steps:
Extracting three sub-categories of behavioral mechanisms, psychological phenomena and mental diseases from the large classes of psychiatry and psychology in the medical term library MeSH, and extracting all the terms contained in the three sub-categories of behavioral mechanisms, psychological phenomena and mental diseases from the MeSH library;
Extracting the diseases related to each term contained in the three sub-categories of the behavioral mechanism, the psychological phenomenon and the mental disease from a disease comprehensive information database MALACARDS, obtaining gene information related to each disease phenotype according to the MALACARDS library, forming a gene set by all the gene information, extracting the molecular association of the gene information on the PPI network based on protein interaction relation PPI data, traversing all the continuous edges in the PPI network, if two genes corresponding to one continuous edge belong to the gene set, reserving the molecular association, traversing each edge, correlating the molecules on all reserved continuous edges, and obtaining a molecular network related to the perception and cognitive behavioral phenotype, wherein the molecular network comprises nodes and continuous edges among the nodes.
Preferably, the construction of the neural, immune, endocrine and microecological related molecular network comprises:
Collecting single-cell histology expression data of various organs, tissues and cells of a human from a human single-cell database HCL, determining tissue organs related to a nervous system, an immune system, an endocrine system and a micro-ecological system from the HCL library based on medical basic knowledge, and combining relations among the organs, the tissues, the cells and genes in the HCL library to obtain the cells and related genes related to the nervous system, the immune system, the endocrine system and the micro-ecological system;
And extracting molecular association of genes related to the nervous system, the immune system, the endocrine system and the micro-ecological system on the PPI network based on PPI data to obtain a molecular network related to the nerve, the immunity, the endocrine and the micro-ecological, wherein the molecular network comprises nodes and connecting edges among the nodes.
Preferably, the constructing molecular network based on the average shortest path length and the network correlation index of the network are used to evaluate the correlation of the perception cognition correlation phenotype and the molecular network of the nerve, immunity, endocrine and microecology on the whole protein interaction network, respectively, comprising the following steps:
Setting the molecular network related to the perception and cognitive behavioral phenotype as a set A and the molecular network related to nerves, immunity, endocrine and microecology as a set B, and calculating the distance between the set A and the set B on the PPI network according to the following calculation formula:
Wherein SPL (i, j) represents the shortest path length of molecules i and j on the network, |a| and |b| represent the number of molecules in sets a and B, respectively, NR sp (a, B) represents the distance on the PPI network in sets a and B;
The calculation formula of the network correlation NR zs (a, B) of the sets a and B on the PPI network is as follows:
wherein S represents the shortest distance between the sets A and B on the PPI network, < S rand > and sigma (S rand) respectively represent the average value and standard deviation obtained under the condition of random set times, NR zs (A, B) is a negative value, and the smaller the value is, the stronger the correlation is;
And constructing a molecular network database of a molecular association mechanism according to the molecular network association of all perception and cognition related phenotypes, nerves, immunity, endocrine and microecology on the PPI network.
According to the technical scheme provided by the embodiment of the invention, the molecular network related to the cognitive behavior phenotype is constructed by constructing the molecular network related to the nerve, immunity, endocrine and micro-ecological system, so that the correlation of the cognitive behavior and the molecular network of the nerve, immunity, endocrine and micro-ecological system can be effectively evaluated, and the database of the molecular correlation mechanism can be constructed.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of cognitive performance and "neural-immune-endocrine-microecological" molecular association based on a complex network provided by an embodiment of the present invention;
fig. 2 is a schematic diagram of a molecular network for perceiving a cognitive behavioral phenotype according to an embodiment of the present invention, wherein a: a molecular network of behaviors and behavior mechanisms; b: a molecular network associated with mental disorders;
fig. 3 is a schematic diagram of a neural and immune related molecular network according to an embodiment of the present invention, wherein a: a neural molecular network; b: immune-related molecular networks.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary only for explaining the present invention and are not to be construed as limiting the present invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless expressly stated otherwise, as understood by those skilled in the art. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or coupled. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
For the purpose of facilitating an understanding of the embodiments of the invention, reference will now be made to the drawings of several specific embodiments illustrated in the drawings and in no way should be taken to limit the embodiments of the invention.
The embodiment of the invention provides a method for correlating cognitive behaviors with a human body molecular network based on a complex network, wherein the human body ecological molecules comprise nerve-immunity-endocrine-microecological molecules. Mainly comprises the construction of a molecular network related to the cognitive behavioral phenotype, and the construction of a molecular network related to nerves, immunity, endocrine and microecology. The schematic diagram of the association flow between the cognitive behaviors and the nerve-immunity-endocrine-microecological molecules based on the complex network provided by the embodiment of the invention is shown in fig. 1, and the specific processing process comprises the following steps:
(1) Molecular network construction related to cognitive behavioral phenotypes
MeSH phenotype terminology extraction. The medical term library MeSH contains 16 broad classes of medical terms such as anatomy (Anatomy), organism (organs), disease (Diseases), and compounds and drugs (Chemicalanddrugs), among others. The terminology related to the sensory and cognitive behavioral phenotypes of interest in the embodiments of the present invention is primarily contained in the sixth category, namely psychiatry and psychology (Psychiatryandpsychology). From this broad class, three sub-classes were identified through artificial verification that are perceptually related to the cognitive behavioral phenotype, namely behavioral and behavioral mechanisms, psychological phenomena and mental disorders, and therefore 1014 terms contained in these three sub-classes were extracted from the MeSH term library, as the results in table 1 below.
Table 1: terms related to cognitive behavioral phenotypes
And (5) constructing a phenotype association molecular network. The three types of diseases related to terms are extracted from the disease comprehensive information database MALACARDS respectively to obtain 427 diseases, gene information related to the disease phenotypes is obtained from the MALACARDS library, 880 genes are obtained in total, and all the gene information forms a gene set. Finally, molecular association of these genes on the PPI network was extracted based on Protein-roteininteractions (PPI) data, in particular: and traversing all the continuous edges in the PI network, if two genes corresponding to one continuous edge belong to the set A, reserving the molecular association, and finally taking all reserved continuous edges as the molecular association by traversing each edge. The extraction results are shown in Table 2 below.
Table 2: molecular networks related to sensory and cognitive behavioral phenotype terms
Thereby obtaining a molecular network related to the perception and cognitive behavioral phenotype, wherein the molecular network comprises nodes and connecting edges among the nodes.
Fig. 2 is a schematic diagram of a molecular network for sensing a cognitive behavioral phenotype according to an embodiment of the present invention. The behavior and behavior mechanisms and mental disorder related molecular networks are respectively drawn by using complex network analysis software Cytoscape as shown in fig. 2A and 2B. FIG. 2A shows a molecular network of behavior and behavior mechanisms, which includes 339 nodes and 708 links, with node averages 4.1770; fig. 2B shows a mental disorder related molecular network comprising 1142 nodes and 4609 links, the average degree of the nodes being 8.0718.
(2) Neural, immune, endocrine and microecological related molecular network construction
Single cell histology expression data for various organs, tissues and cells of humans is collected in the human single cell database (HCL). Thus, based on the basic knowledge of medicine, the tissue organs involved in the nervous system, immune system, endocrine system, and micro-ecosystem, namely, the tissue organs involved in the nervous system, such as brain (brain), spinal cord (spinal-cord), and pituitary gland (hypophysiscerebri), are determined from the human single cell database (HCL); the immune system involves organs such as spleen (spleen), lymph (lympho), thymus (thymus) and lymph-bone marrow (lympho-myeoid); endocrine systems involve tissues and organs such as adrenal gland (adrenal-gland), pancreas (pancreas), and thyroid gland (thyroid); the micro-ecological system relates to tissues and organs such as the intestines (intestine) and the stomach (stomachs). Finally, the four system-related cells and associated genes were extracted from the HCL database in combination with relationships between organs, tissues, cells and genes.
And extracting molecular association of genes related to the nervous system, the immune system, the endocrine system and the micro-ecological system on the PPI network based on PPI data to obtain a molecular network related to the nerve, the immunity, the endocrine and the micro-ecological, wherein the molecular network comprises nodes and connecting edges among the nodes. The following results were obtained as shown in Table 3.
Table 3: associated molecular networks of nervous, immune, endocrine, and microecological systems
Fig. 3 is a schematic diagram of a neural and immune related molecular network according to an embodiment of the present invention, as shown in fig. 3A and 3B. FIG. 3A shows a neural-related molecular network, which includes 4095 nodes and 23964 links, with node averages 11.7040; fig. 3B shows an immune system-related molecular network comprising 5206 nodes and 47144 links, with an average node size of 18.1114.
(3) Network-based analysis of cognitive behaviors and molecular association mechanisms of neural-immune-endocrine-microecological
Molecular network correlations of perceptive cognitive-related phenotypes with neural, immune, endocrine and microecological interactions over the whole protein interaction (PPI) network are assessed using the network average shortest path length (i.e., network shortest distance) and the network correlation index z-score, respectively. The nature of the calculation of the correlation of the molecular network is to evaluate the correlation of two molecular sets on the PPI network, taking the molecular set a and the molecular set B as an example, and evaluating the network correlation (Networkrelevance, NR) of the sets a and B with the average shortest path length of the network, the formula is as follows:
where SPL (i, j) represents the shortest path length of molecules i and j on the network, |a| and |b| represent the number of molecules in sets a and B, respectively. The network shortest distance is a positive value, and smaller values indicate more relevant. The calculation formula of the network correlation z-score is as follows:
Wherein S represents the shortest distance between the sets A and B on the PPI network, and < S rand > and sigma (S rand) respectively represent the average value and standard deviation obtained under the random 10000 times. The z-score is negative, with smaller values indicating stronger correlation.
And respectively evaluating the molecular network correlation between the perception and behavior phenotypes and the nerve, immunity, endocrine and microecological systems by using the two network correlation indexes, and constructing a database of a molecular correlation mechanism according to the molecular network correlation of all the perception and cognition related phenotypes and the nerve, immunity, endocrine and microecological on the PPI network.
The method of the embodiment of the invention obtains the following results:
Table 4: molecular networks related to sensory and cognitive behavioral phenotype terms
Since the molecular association and molecular network of the psycho-phenomenological phenotype is not found in the PPI network, the molecular network association of psycho-phenomenological and neural, immune, endocrine and microecological interactions cannot be obtained. As can be seen from the results in table 4, both the mean shortest distance and network correlation z-score showed a strong correlation with both neurological, immune, endocrine and microecological and a relatively similar correlation with these systems for both phenotypes, i.e. behavioral and behavioral mechanisms and mental diseases. This suggests that the four human systems of neural, immune, endocrine and microecological and cognitive behavioral phenotypes are all related on the molecular network. This suggests that we need to incorporate all four human systems into them when constructing a molecular association mechanism database. Finally, the various phenotypes, human systems, tissues, cells and gene molecules obtained in tables 1, 2, 3 and 4 and the complex molecular associations between them were used as a molecular association mechanism database of cognitive behavioral phenotypes with nerves, immunity, endocrine and microecology.
In summary, the embodiment of the invention constructs a molecular network related to cognitive behavioral phenotype for the first time, constructs a molecular network related to nerve, immunity, endocrine and micro-ecological system by combining single cell data for the first time, evaluates the correlation of cognitive behaviors and the molecular network of the nerve, immunity, endocrine and micro-ecological system by using a network computing method for the first time, and constructs a database of molecular correlation mechanisms of the cognitive behaviors and the nerve, immunity, endocrine and micro-ecological system.
Those of ordinary skill in the art will appreciate that: the drawing is a schematic diagram of one embodiment and the modules or flows in the drawing are not necessarily required to practice the invention.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus or system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, with reference to the description of method embodiments in part. The apparatus and system embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
The present invention is not limited to the above-mentioned embodiments, and any changes or substitutions that can be easily understood by those skilled in the art within the technical scope of the present invention are intended to be included in the scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.
Claims (1)
1. A method for associating cognitive behaviors with a human molecular network based on a complex network is characterized by comprising the following steps:
constructing a molecular network related to perception and cognitive behavioral phenotypes;
constructing a molecular network related to nerves, immunity, endocrine and microecology;
Based on the constructed molecular network, the average shortest path length of the network and the network correlation index are utilized to respectively evaluate the correlation between the perception cognition related phenotype and the molecular network of the nerve, immunity, endocrine and microecology on the whole protein interaction network, so as to construct a molecular network database;
the construction of the molecular network related to the cognitive behavioral phenotype comprises the following steps:
Extracting three sub-categories of behavioral mechanisms, psychological phenomena and mental diseases from the large classes of psychiatry and psychology in the medical term library MeSH, and extracting all the terms contained in the three sub-categories of behavioral mechanisms, psychological phenomena and mental diseases from the MeSH library;
Extracting the diseases related to each term contained in the three sub-categories of the behavioral mechanism, the psychological phenomenon and the mental disease from a disease comprehensive information database MALACARDS, obtaining gene information related to each disease phenotype according to a MALACARDS library, forming a gene set by all the gene information, extracting the molecular association of the gene information on a PPI network based on protein interaction relation PPI data, traversing all the continuous edges in the PPI network, if two genes corresponding to one continuous edge belong to the gene set, reserving the molecular association, traversing each edge, correlating the molecules on all reserved continuous edges to obtain a molecular network related to the perception and cognitive behavioral phenotype, wherein the molecular network comprises nodes and continuous edges among the nodes;
the construction of the molecular network related to nerves, immunity, endocrine and microecology comprises the following steps:
Collecting single-cell histology expression data of various organs, tissues and cells of a human from a human single-cell database HCL, determining tissue organs related to a nervous system, an immune system, an endocrine system and a micro-ecological system from the HCL library based on medical basic knowledge, and combining relations among the organs, the tissues, the cells and genes in the HCL library to obtain the cells and related genes related to the nervous system, the immune system, the endocrine system and the micro-ecological system;
Extracting molecular association of genes related to the nervous system, the immune system, the endocrine system and the microecological system on a PPI network based on PPI data to obtain a molecular network related to the nerve, the immunity, the endocrine and the microecological system, wherein the molecular network comprises nodes and connecting edges among the nodes;
The molecular network based on construction utilizes the average shortest path length of the network and the network correlation index to evaluate the correlation of the perception cognition correlation phenotype and the molecular network of the nerve, immunity, endocrine and microecology on the whole protein interaction network, and comprises the following steps:
Setting the molecular network related to the perception and cognitive behavioral phenotype as a set A and the molecular network related to nerves, immunity, endocrine and microecology as a set B, and calculating the distance between the set A and the set B on the PPI network according to the following calculation formula:
Wherein SPL (i, j) represents the shortest path length of molecules i and j on the network, |a| and |b| represent the number of molecules in sets a and B, respectively, NR sp (a, B) represents the distance on the PPI network in sets a and B;
the calculation formula of the network correlation NR zs (a, B) of the sets a and B on the PPI network is as follows:
Wherein S represents the shortest distance between sets a and B on the PPI network, < S rand > and σ (S rand) represent the average value and standard deviation, respectively, obtained in the case of random set times, NR zs (a, B) is negative, and a smaller value represents a stronger correlation;
And constructing a molecular network database of a molecular association mechanism according to the molecular network association of all perception and cognition related phenotypes, nerves, immunity, endocrine and microecology on the PPI network.
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