Bioinformatics

Our bioinformatics capability offers services to both academic and industry researchers.

Our senior bioinformatician, Dr. Esmaeil Ebrahimie, has over 20 years of experience in bioinformatics, machine learning, and biostatistics. He has a proven track record in the innovative application of machine learning, advanced statistical pipelines, and high-performance computing in biomedical research and drug repurposing.

Since 2015, his expertise in omics and next-generation sequencing data analysis, and machine learning has supported numerous competitive research grant applications.

Dr. Ebrahimie is an expert in analysing large and complex biomedical datasets, including single-cell and virome data, utilizing cloud-based high-performance computing resources. He currently manages virtual machines for single-cell analysis and machine learning through projects like the National Collaborative Research Infrastructure Strategy (NCRIS) via the Nectar Research Cloud project, Pawsey Supercomputing (a government-supported national facility), and Oracle Research.

More information about Dr. Esmaeil Ebrahimie can be found on our people page.

We can offer:

  • bioinformatics services on an hourly basis
  • data analysis, visualisation and exploration
  • high performance computing
  • expert advice in experimental design, data analysis, visualisation and publication
  • participation in grant applications as a Chief Investigator (CI), or Associate Investigator (AI).

The main areas where we can help you with bioinformatics, machine learning (pattern discovery) and multi-omics data analysis are:

  • general Bioinformatics Advice:
    • software usage
    • basic QC
    • read-mapping
    • variant calling
    • machine learning with python and rapidminer
    • statistics (Minitab, R, and Python) etc.
  • RNA seq analysis
  • network, GO, and enrichment analysis
  • phage display (MiSeq) data analysis
  • de novo assembly
  • single cell analysis
  • virome analysis
  • microbiome analysis
  • alternative splicing
  • meta-analysis
  • epigenomics-methylation
  • Association rule mining
  • epigenomics-RRBS
  • multivariate analysis
  • multi-omics analysis
  • small RNA seq analysis
  • long read analysis
  • cloud virtual machine setup
  • lanuscript preparation
  • grant application
  • cloud virtual machine setup and training.

LIMS-HPC

LIMS-HPC is a High Performance Computer specialised for genomics research. It has over 340 software packages available to researchers, most from genomics and related fields.

Access LIMS-HPC

La Trobe HPC (Intersect)

La Trobe provides university-wide access to HPC that can be used for Genomics research.

More information on Intersect-HPC

Cloud-based high performance computing virtual machines

National Collaborative Research Infrastructure Strategy (NCRIS) through the Nectar Research Cloud project.

Pawsey Supercomputing is a government-supported national facility for high-performance computing.

Geneious

La Trobe University supports Geneious licenses for its researchers.

Request access to Geneious (La Trobe login required)

The genomics platform has developed a number of data visualisation tools that allow you to gain insights into your datasets and present them to the wider community.

These tools are available to all La Trobe researchers. We can upload your data to these tools upon request.

JBrowse genome browser

A tool for visualising genomic data aligned to the reference sequence. These can include: read-mapping, gene-models, methylation, SNP, small-RNA and many more.  It supports a wide range of data formats and custom plugins can be installed to add further functionality.

Data can initially be secured to your lab-group while you to develop your research.

General public access can be enabled later to promote your research in an accessible and discoverable form.

Access Genome Browser

RNAseq database

A tool to discover genes of interest and visually present their expression levels to aid understanding.

Data can initially be secured to your lab-group while you to develop your research.

General public access can be enabled later to promote your research in an accessible and discoverable form.

Access RNAseq Database

Quality is an integral part of our research platform's purpose and value. We are committed to providing our customers, industry partners and academic collaborators with services and products that are of high quality, consistent and compliant.

Our platforms strive to be recognised and trusted by researchers as an excellent research service provider that constantly meet or exceed customer expectations. To achieve this, we have implemented a Quality Management System (QMS) across Research Platforms that operates on all our campuses.

Our QMS is aligned to the AS/NZS ISO 9001:2016 standard and the University’s Research 2030: Research and Engagement Plan 2020-2024. In alignment with the ISO standard, efforts are focused on understanding customer needs and ensuring their satisfaction, as well as continuously improving service provision in the pursuit of research excellence. The services provided by Research Platforms are also underpinned by our cultural qualities: to be connected, innovative, accountable and caring.

The Research Platforms quality policy embraces the following key principles:

  • Building a mutually beneficial relationship with customers, ensuring their long-term success through the understanding of, and meeting, their needs.
  • Nurturing a quality mindset with the objective of providing services that are trusted and preferred by internal and external researchers and deliver on our Research Plan Objective 1: Research Excellence.
  • Complying with all relevant laws and regulations as well as internal policies and requirements.
  • Continuously challenging all Research Platforms to improve the QMS to prevent quality incidents, eliminate errors, accelerate research, and ensure high quality data through efficient business processes, best-practice and well-defined goals.
  • Encouraging involvement in quality responsibilities amongst all Research Platform personnel, researchers and relevant third parties through quality standards, education, training and mentoring, supervision and effective internal and external communication.

Our platforms are currently seeking to achieve ISO9001 accreditation as part of their commitment to their customers. Work to obtain verification by independent third-party certification bodies is ongoing.

The platform’s contributions to research outputs (e.g., publications, presentations, posters) should be acknowledged where possible. These contributions could include:

  • paid technical help and services
  • accessing research equipment
  • scientific advice
  • writing assistance.

Proper acknowledgement enables us to demonstrate our value to the research community and highlight our impact on research excellence, which is critical to securing continued funding for our services. Our staff are also researchers with extensive experience and citing them helps to advance their careers.

In cases where substantial intellectual and experimental contributions were made by platform staff, co-authorship must also be offered in accordance with the Australian Code for the Responsible Conduct of Research, regardless of whether payment was made for the services. Researchers should also notify the platform of any publications arising from the support provided by our staff, regardless of whether a co-authorship is offered.

Learn more about how to acknowledge us:

All publications resulting from the use of our services and facilities should include this acknowledgement:

‘The authors acknowledge the La Trobe University [Platform Name] for [support received].’

e.g., The authors acknowledge the La Trobe University Proteomics and Metabolomics Platform for the provision of instrumentation, training and technical support.

OR

e.g., The authors acknowledge the La Trobe University Statistics Consultancy Platform for providing advice on statistical analysis.

If you received significant assistance, guidance or help from our platform staff, or where staff have personally generated research data, they should be acknowledged by name:

‘The authors thank [Staff Name] from the La Trobe University [Platform Name] for [his/her/their] support and guidance in this work.’

e.g., The authors thank [Staff Name] from the La Trobe University Proteomics and Metabolomics Platform for collecting and analysing data for proteomics studies, shown in Figure X.

If a platform staff contribute more than just routine techniques or advice, they should be invited to be a co-author on the publications that describe the data. This applies to the development or adaptation of protocols to suit specific experiments, samples or materials, (re)design of experiments, and extensive data analysis and interpretation.

Co-authorship is independent of whether payment was made for the work/ service.

Access

Our bioinformatics services are available to both academic researchers and industry partners, including pharmaceutical and biotechnology companies.

  • La Trobe researchers
    We provide our staff and students with up to 1.5 hours free consultation per project. Subsequent hours and works are charged at a subsidised rate.
  • External researchers and industry partners
    Service is available on a fee-per-hour basis.  Contact us with your requirements and our team will provide a quote and timeline for your project. We can also arrange for a consultation as required.

Contact us

For more information and to discuss your requirements, contact us at genomics platform.