Bioinformatics Data Modelling and Analysis

Abstract

The Brain-Like Artificial Intelligence (BLAI) is pioneered by Prof.Nikola Kasabov and here it is applied to a specific application.

Figure. Schematic representation of the SNN system for bioinformatics data modelling and analysis.

This SNN system propose novel research which is current under development. This novel system for bioinformatics data analysis is being applied to:

  • Static and Dynamic Transcriptomics Data Modelling and Analysis
  • Metabolomics Data Modelling and Analysis
  • Nutrigenomics Data Modelling and Analysis
  • Feature Selection Methods for Gene Expression Data Analysis

This SNN system can also be used to understand the biochemical mechanims that govern synaptic plasticity in the human brain and regulate cognitive by mean of glutamatergic and GABAergic bidirectional activity.


Related Papers, Patents and Benchmarking  

The proposed methods and systems, when compared with traditional statistical and machine learning methods, showed superior results in the following aspects:

  1. Better data analysis and classification accuracy;
  2. Better visualisation of the created models, with a possible use of VR;
  3. Better understanding of the data and the processes that are measured through a gene interaction network;
  4. Enabling new information and knowledge discovery through meaningful interpretation of the models and the genetics process that regulate the data.

See also some of the related papers:

Kasabov, N., Scott, N. M., Tu, E., Marks, S., Sengupta, N., Capecci, E., Othman, M., Gholoami Doborjeh, M., Murli, N., Hartono, R., Espinosa-Ramos, J. I., Zhou, L., Alvi, F., Wang, G., Taylor, D., Feigin, V., Gulyaev, S., Mahmoud, M., Hou, Z. G., Yang, J. (2016). Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: design methodology and selected applicationsNeural Networks78, 1-14

Espinosa-Ramos, J.I., Capecci, E., Kasabov, N. (2017). A Computational Model of Neuroreceptor Dependent Plasticity (NRDP) Based on Spiking Neural Networks. IEEE Transactions on Cognitive and Developmental Systems. Special Issue on Spiking Neural Networks. Available online 22/11/2017. DOI:10.1109/TCDS.2017.2776863

Koefoed, L., Capecci, E. and Kasabov, N. (2018, July). Time Series Analysis of rVSV-ZEBOV trial data using TMRMR-C and NeuCube. 2018 International Joint Conference on Neural Networks (IJCNN). Rio De Janeiro, Brazil, 8-13 July (accepted). IEEE


R&D System

For this project, an R&D system has been developed based on NeuCube. The system can be obtained subject to licensing agreement.


Developers and Students

The developers of this project are:

Dr Elisa Capecci