Pankhuri Sharma

Manav Rachna International Institute of Research and Studies, India

Abstract Title: Eyeballing the Brain with Neuroinformatics

Biography: Pankhuri Sharma is currently pursuing a Ph.D. in Neuroinformatics at Manav Rachna International Institute of Research and Studies, Faridabad, Haryana, India. Her research focuses on the molecular mechanisms of Huntington’s Disease, with an emphasis on peptide design, protein–peptide interactions, molecular docking, and molecular dynamics simulations. She has previously gained research experience at the Division of Microbiology, Indian Agricultural Research Institute (IARI), New Delhi, and the Department of Plant Molecular Biology, University of Delhi, South Campus. Her broader interests lie in integrating computational tools with neuroscience to investigate novel therapeutic strategies.

Research Interest: The human brain, as marvellous as it is, creates temporally and spatially complex signals and patterns to regulate proper functioning of the body. Therefore, neuroscience data is massive, multidimensional and noisy. Analysis of data of this volume has been a complicated task with existing analytical methods. Neuroinformatics, a discipline conceived to overcome this issue, is a culmination of neuroscience and computer science. Neuroinformatics thrives on enormous, dense and multifaceted data to isolate significant information. Neuroimaging using neuroinformatics is a powerful tool for understanding brain function and diagnostics. This study focusses on presenting the advantages and drawbacks of current advances in neuroinformatics-based neuroimaging tools. The neuroinformatic tool, Global Tree Reconstruction System (GTree) is an open-source software created specifically to digitally reconstruct neurons from a large dataset. The highly automated algorithm is designed to reduce manual interference, screen errors and reconstruct neurons as close to reality. Another tool, Neuprint, allows reconstruction of connectomes, which are a depiction of neurons and chemical synapses from large volume of neural tissues. It contains a web interface and a programmers API. It is designed to enable scientists globally get answers to their complex connectome related queries using a browser. It is integrated with connectomics database, neo4j, and Cypher, a query language, and is open to further integrations as well. Neurodesk is a platform that contains suites of numerous neuroimaging software. The interface has a virtual desktop, command line and is compatible with computational notebook. This not only allows portability and flexibility but also accessibility to accurate neuroimaging analysis. Advanced machine learning, artificial intelligence and data analytics have allowed researchers to study the intricacies of neural networks, and convert scientific findings into real-life applications. This study attempts to exhibit, while assessing, these advances, their utilisation for neuroimaging along with their drawbacks. Key words: Neuroinformatics, Neuroimaging, reconstruction, Brain, Neurodesk