Skip to content

Epigenetic and Transcriptomic Regulations in Brain Disorders

Oct 2026 · Royal Society of Chemistry eBooks · 365 references
Epigenetics and DNA Methylation

Abstract

Epigenetic and transcriptomic mechanisms are pivotal to the human brain’s complexity, adaptability, and function, regulating gene expression without altering the DNA sequence. These processes, involving DNA methylation, histone modifications, non-coding RNAs, alternative RNA splicing, and regulatory RNAs, enable the brain to respond to developmental cues, environmental factors, and neural activity, shaping neuronal identity, synaptic plasticity, and cognitive processes. Dysregulation of the epigenetic and transcriptomic mechanisms is associated with neurodevelopmental disorders such as autism spectrum disorder and Rett syndrome, psychiatric conditions like schizophrenia and major depressive disorder, and neurodegenerative diseases including Alzheimer’s, Parkinson’s, and Huntington’s. This chapter explores how epigenetic and transcriptoincludmic systems interact through feedback loops and system-level regulation to maintain neural resilience. Advanced tools, such as single-cell sequencing, spatial transcriptomics, and CRISPR-based gene editing, allow precise mapping of gene expression across specific cell types and brain regions. Multi-omics integration enhances our understanding of brain disorders, advancing diagnosis, prevention, and personalized treatment strategies. Targeting these reversible molecular changes offers significant therapeutic potential, though challenges like cellular heterogeneity, intervention timing, and clinical translation persist.

View source

Similar papers

#computer vision Conference Aug 2008

A Preliminary Roadmap for Empirical Research on Agile Software Development

Some claim that especially in the field of agile software development the research lags years behind of the practice. In this paper, we characterize the status and main challenges for research on agile software development, and propose a preliminary roadmap, focusing on providing more empirical research, primarily on e...

Torgeir Dingsøyr, T. Dybå, P. Abrahamsson · 92 citations · ⚡7
#computer vision Book Open access Mar 2017

On the Unhappiness of Software Developers

The results indicate that software developers are a slightly happy population, but the need for limiting the unhappiness of developers remains, and 219 factors representing causes of unhappiness while developing software are identified.

D. Graziotin, Fabian Fagerholm, Xiaofeng Wang et al. · 84 citations · ⚡6
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Review Apr 2024

AI-powered Code Review with LLMs: Early Results

The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.

Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al. · 62 citations · ⚡3
#computer vision Conference Aug 2008

Scrum in a Multiproject Environment: An Ethnographically-Inspired Case Study on the Adoption Challenges

Agile methods continue to gain popularity. In particular, the Scrum method appears to be on the verge of becoming a de-facto standard in the industry, leading the so called Agile movement. While there are success stories and recommendations, there is little scientifically valid evidence of the challenges in the adoptio...

A. Marchenko, P. Abrahamsson · 59 citations · ⚡11

Related blog posts

Microsoft Research Blog Oct 15, 2026

Proof-based general-purpose computing with Magnetar

Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.