Kosar Hooshmand

Kosar is a molecular and computational biologist with an interest in Genomics, Transcriptomics and Next Generation Sequencing technologies. She graduated with a MSC in Biochemistry at Ferdowsi University of Mashhad, Iran in 2016. She joined the ForeFront Bioinformatics & Statistic research group as an affiliate in 2018 and started her PhD in 2020 at the University of Sydney.



Dr Boris Guennewig, Prof Glenda Halliday and A/Prof Greg sutherland


  • Genetics
  • Cellular & Molecular Biology
  • Biomarkers

Neurodegeneration of interest:

AD, FTD, PD, ALS, Dementia, Ageing

Specific Skills:

  • Bioinformatics
  • Molecular Biologist
  • Biochemist
  • Cell culture
  • Flow cytometry

Project - Transcriptomics in Neurodegenerative Disease

Research Project Abstract

Study of transceiptomics (mRNAs, long ncRNAs, small ncRNAs) and their targets to provide insight into their crucial role and offer approaches for the treatment of Neurodegenerative Diseases (NDs). This is possible through analysing sequencing data provided by deep sequencing techniques. The project is expected to be funded: 2020- 2023.

Research Project Description

So far there are no effective biomarkers for monitoring Neurodegenerative Diseases (NDs) and their progression. My research focuses on the identification and characterization of genetic variation and transcriptional changes connected with different pathways that will identify the pathogenesis of AD, PD, FTD, and ALS, providing information on their role/s in NDs and the potential for disease and stage specific diagnostic biomarkers for each condition.

Disease area:

AD, PD, FTD, ALS, Dementia, Ageing

Aims and Objectives:

For this purpose, I will access the short read archive (SRA) to determine predictive NDs genetic variants and their biological function and protein interactions.

  • Metadata and Sample query
  • Quality control and trimming process
  • Mapping all sequences to transcriptome using Kallisto
  • Prediction of alternative splicing events using SUPPA2
  • Prediction of RNAs being differentially expressed Using Different R Bioconductor packages
  • Prediction of novel biomarkers using machine learning approaches