About this Research Topic
Given the success of the Research Topic Volume I "Identifying the Key Pathogenic Factors of Neurological Disorders by Integrating Multi-omics Data", we are pleased to launch a second volume for further submissions. https://www.frontiersin.org/research-topics/24245/identifying-the-key-pathogenic-factors-of-neurological-disorders-by-integrating-multi-omics-data
Currently, the research on human neurological disorders is inadequate in both etiological explanation and drug development and clinical treatment, because of their complex molecular mechanisms, relatively rare clinical samples, and data resources. For example, there is a long-standing controversy about the pathogenesis of Alzheimer's disease between the amyloid β-peptide (Aβ) deposits model and microbial infection theory. With the rapid development of high throughput technology, it’s getting easier to low-cost access multi-mics, including genome variations, transcriptome expression level, alternative splicing, epigenome, proteome, metabolome, microbiome, etc, data by the wet-lab technique. A range of analytical approaches through integrating multi-omics data from different resources (e.g. xQTL, pGWAS, and MR) have a great enhanced understanding of the molecular mechanism in human complex diseases. However, these studies by integrating multi-omics data in the human nervous system are limited, which is not only because of the overall scarcity of related studies but also because of relatively rare data resources on human neurological disorders.
In summary, the current challenge for understanding the molecular mechanisms of human nervous system functions and neurological disorders is to 1) develop computational approaches and analysis pipeline for integrating multi-omics data of the human nervous system and neurological disorders; 2) build the databases to store and enrich multi-omics data of human nervous system and neurological disorders; 3) causal inference of environmental pollution affecting neurological diseases based on multi-omics data; 4) drug discovery in the field of the nervous system by multi-omics computational approaches.
Therefore, we propose to conduct a Research Topic on “Identifying the Key Pathogenic Factors of Neurological Disorders by Integrating Multi-omics Data”. The subtopics include, but are not limited to:
(1) Determination of the etiology of human neurological diseases using multi-omics data.
(2) Statistical approaches and analysis pipeline for integrating multi-omics data in the small-scale sample.
(3) Databases for storing multi-omics data of the human nervous system and neurological disorders.
(4) Causal inference of environmental pollution affecting neurological diseases.
(5) Drug discovery in the field of the nervous system based on computational approaches.
Currently, the research on human neurological disorders is inadequate in both etiological explanation and drug development and clinical treatment, because of their complex molecular mechanisms, relatively rare clinical samples, and data resources. For example, there is a long-standing controversy about the pathogenesis of Alzheimer's disease between the amyloid β-peptide (Aβ) deposits model and microbial infection theory. With the rapid development of high throughput technology, it’s getting easier to low-cost access multi-mics, including genome variations, transcriptome expression level, alternative splicing, epigenome, proteome, metabolome, microbiome, etc, data by the wet-lab technique. A range of analytical approaches through integrating multi-omics data from different resources (e.g. xQTL, pGWAS, and MR) have a great enhanced understanding of the molecular mechanism in human complex diseases. However, these studies by integrating multi-omics data in the human nervous system are limited, which is not only because of the overall scarcity of related studies but also because of relatively rare data resources on human neurological disorders.
In summary, the current challenge for understanding the molecular mechanisms of human nervous system functions and neurological disorders is to 1) develop computational approaches and analysis pipeline for integrating multi-omics data of the human nervous system and neurological disorders; 2) build the databases to store and enrich multi-omics data of human nervous system and neurological disorders; 3) causal inference of environmental pollution affecting neurological diseases based on multi-omics data; 4) drug discovery in the field of the nervous system by multi-omics computational approaches.
Therefore, we propose to conduct a Research Topic on “Identifying the Key Pathogenic Factors of Neurological Disorders by Integrating Multi-omics Data”. The subtopics include, but are not limited to:
(1) Determination of the etiology of human neurological diseases using multi-omics data.
(2) Statistical approaches and analysis pipeline for integrating multi-omics data in the small-scale sample.
(3) Databases for storing multi-omics data of the human nervous system and neurological disorders.
(4) Causal inference of environmental pollution affecting neurological diseases.
(5) Drug discovery in the field of the nervous system based on computational approaches.
Keywords: Neurological disorders, Multi-mics data, Bioinformatics, Data mining, Molecular mechanism, Drug discovery
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