i want to develop a ml tool for learning and exploring gene expression through development using the generalized functions for querying data on any gene through multiple developmental stages and brain span in humans and mouse…

now, getting into the part of resources, The Allen Institute for Brain Science is a research facility dedicated to providing the scientific community with tools and resources for exploring the brain. Over the last 10 years, in collaboration with research labs across the world, the Institute has openly released numerous datasets, including data from developing brains, diseased brains, mouse, primate, and human brains.

These datasets, available in the public domain, provide an open playground for neuroscientists of all experiences, from high-school students to academic researchers, to explore the brain and “see for themselves” the discoveries reported in the scientfic literature. Much in the same way that the ImageNet and MNIST datasets are used as both a benchmark and educational resource in the machine learning community, the Allen Brain datasets can be used as a reference to verify findings from neuroscience literature and offer an interactive platform to learn more about the brain.

In this project, I use the Allen Brain datasets, and in particular BrainSpan, the developing human brain dataset, to describe important concepts and findings in developmental neurobiology. It has been written to accommodate readers of all backgrounds and is designed to encourage interactivity. 

Developing Human Brain – BrainSpan

BrainSpan contains gene expression data within regions of the developing human brain. Gene expression data is collected through transcriptome profiling, microarray analysis and in-situ hybridisation which are explained below. The dataset also provides reference atlases; images of the developing human brain annotated by brain strucucture.

*Transcriptome *

Advantages:

  • Complete list of genes
  • Close separation in donor ages

Disadvantages:

  • Brain structures less specific than microarray data

Microarray

Advantages

  • Fine spatial resolution – samples from very specific brain regions.

Disadvantages

  • Only 4 donors (so only 4 developmental stages: 15pcw, 16pcw or 21pcw)
  • ISHThe BrainSpan dataset also contains in-situ hybridisation data…Advantages:
    • Can visually see expression in brain slice
    Disadvantages:
    • Not quantitative
    Developing Mouse Brain AtlasLike BrainSpan, this dataset contains gene expression across development stages of the developing mouse brain.Documentation/Useful LinksAllen Brain Atlases Home Page – Central hub for exploring all Allen datasets.AllenSDK Github repository – Useful for seeing explicity how queries are parsed by the sdk.API Online Documentation – Links to documentations for different API subclasses (e.g. ImageDownloadApi, OntologiesApi)AllenSDK Examples – Sample of Jupyter notebooks guiding through using aspects of the AllenSDK.API Class Lists – Lists all classes used by the Allen API. Useful for finding class names, attrubutes and associations needed for constructing RMA queries.BrainSpan Data Documentation – Links to white papers detailing methodology used to create BrainSpan data.BrainSpan API Documentation – Explanations and examples of accessing BrainSpan data using the API.RMA Guide – Explains components of RESTful Model Access queries used to access Allen data.Services Documentation – Useful for constructing service RMA queries. Lists parameters and example queries.Developing Mouse API Documentation – Explanations and examples of accessing the developing mouse brain atlas data.Developing Mouse Annotation Volumes – Links to 3D volumetric data files for the developing mouse brain. These files can be used to load a coordinate system for 2/3D gene expression plots.
  • Developmental Neurobiology”It has long been recognized that the life history of a neuron can be characterized by a temporal progression of transitions that may be conveniently (albeit somewhat arbitrarily) viewed as a discrete series of neurogenetic steps or stages through which virtually all cells must pass. Included among these steps are induction, proliferation, migration, restriction and determination, differentiation (expression), the formation of axonal pathways and synaptic connections, and the onset of physiological function. ” – Oppenheim 1991It is an incredible feat of biology to transform a single-celled zygote into a fully-developed adult human being – an end-product that has the ability to perceive its own environment and engage in conscious thought. To create such a complex organism, the developing embryo must undergo a series of precisely timed and controlled developmental processes.A natural starting point for the development of the nervous system is during a process of gastrulation in which cells in the early embryo start to differentiate to form neural tissue. However in the interest of using Allen Brain data, this article begins at a few developmental stages after this point when the embryo has folded to form the neural tube.
  • Neurogenesis[NEUROGENESIS INTRODUCTION]The human brain is thought to consist of over 80 billion neurons.Neurogenesis is an intricately controlled process. Too few neurons produced may result in microcephaly; too many can lead to. Too many excitatory neurons than inhibitory neurons can also lead to autism. To avoid these defects, evolution has developed genetic machinary to balance these factors.Some of the genes responsible for controlling the process of creating excitatory neurons in the cortex, were identified and investigated by Englund et al. in a study published in 2005.
  • image.png
  • so,thus creating visualisations and an educational resource for learning about developmental neurobiology using real data.
  • image.png
Guna_prashanth
Author: Guna_prashanth

UG student in ECE ,working on ML tool geneexpression ,Enthusiastic computer science specialist.Seeking to use proven coding skills to deliver efficient development solutions.

Categories: Project

Guna Durga Prashanth Thota

Guna_prashanth

UG student in ECE ,working on ML tool geneexpression ,Enthusiastic computer science specialist.Seeking to use proven coding skills to deliver efficient development solutions.

3 Comments

Sreesurya Aitha · September 23, 2020 at 12:20 pm

Awesome work & sounds great.

P SAMPREETH CHANDRA · September 24, 2020 at 4:15 am

A very good brief and Interesting one 👌

Leave a Reply

Your email address will not be published. Required fields are marked *