Bioinformatics approach to Cryptosporidium identity: database prospects

Summary

The Bioinformatics approach to Cryptosporidium identity: database prospects study will examine (i) the applicability of web based platform to clinical and field data and (ii) develop an automated approach to identification and annotation to sequences.

Supervisor

Professor Jan Slapeta.

Research location

Sydney School of Veterinary Science

Program type

PHD

Synopsis

Intracellular single-cell parasites of the genus Cryptosporidium infect vertebrates, including humans, worldwide. Cryptosporidiosis is self-limiting disease in healthy hosts but represents a life-threatening problem in immunocompromised individuals for which there is no effective treatment. The diversity of the genus Cryptosporidium is mystifying for many biologists and even more so for non-specialists nevertheless is critical for understanding the epidemiology of the disease. A DNA approach to identity stands on the implicit assumption that the reference databases used for comparison are sufficiently complete and feature rich with annotated entries. However, the uncertain taxonomic reliability and annotations in public DNA repositories (GenBank) form a major obstacle to sequence-based species identification. Finally yet importantly, a huge gap exists between the number of described names and number of identified genotypes. The closure of this gap represents a prime challenge for the decades to come. The Bioinformatics approach to Cryptosporidium identity: database prospects study will examine (i) the applicability of web based platform to clinical and field data and (ii) develop an automated approach to identification and annotation to sequences. The web portal will aim to provide a common gateway for analysing Cryptosporidium species and to standardize the terminology of individual isolates. Alignments of the reference sequences from the named species are provided with further detailed annotation of individual species. Furthermore, currently under development is a web based analysis (BLAST, multiple sequence alignment, tree building etc.) as well as an in-house annotation database of sequences to streamline and standardise the process for identification of Cryptosporidium isolates. This presents opportunities for PhD topic projects: (1) Development and implication of bioinformatics algorithms; (2) Database development and application and (3) Research based end-user web based applications.

Additional information

Techniques used in the project:

(1) Development and implication of bioinformatics algorithms

• Computational skills: JAVA, PERL, CGI etc.

(2) Database development and application

• Database management: SQL

(3) Research based end-user web based applications.

• Web development

HDR Inherent Requirements

In addition to the academic requirements set out in the Science Postgraduate Handbook, you may be required to satisfy a number of inherent requirements to complete this degree. Example of inherent requirement may include:

• Confidential disclosure and registration of a disability that may hinder your performance in your degree;
• Confidential disclosure of a pre-existing or current medical condition that may hinder your performance in your degree (e.g. heart disease, pace-maker, significant immune suppression, diabetes, vertigo, etc.);
• Ability to perform independently and/or with minimal supervision;
• Ability to undertake certain physical tasks (e.g. heavy lifting);
• Ability to undertake observatory, sensory and communication tasks;
• Ability to spend time at remote sites (e.g. One Tree Island, Narrabri and Camden);
• Ability to work in confined spaces or at heights;
• Ability to operate heavy machinery (e.g. farming equipment);
• Hold or acquire an Australian driver’s licence;
• Hold a current scuba diving license;
• Hold a current Working with Children Check;
• Meet initial and ongoing immunisation requirements (e.g. Q-Fever, Vaccinia virus, Hepatitis, etc.)

You must consult with your nominated supervisor regarding any identified inherent requirements before completing your application.

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Opportunity ID

The opportunity ID for this research opportunity is 152

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