Arjana Begzati, PhD Student at University of California San Diego

In a recent meeting with Arjana Begzati, she discussed with us about Bioinformatics and Big Data, getting to know us more about her profession and research. Arjana told us how the science of bioinformatics is helping to transform the way we understand and treat disease through the analysis of big biological data.

In the age of digital information, bioinformatics stands as a hope for revolutionizing the diagnosis and prediction of diseases through the use of big data. As we delve into the complex world of molecular and cellular biology, the integration of computer science emerges as a key tool, enabling us to interpret large amounts of data collected from various biological experiments.

Bioinformatics, an interdisciplinary field, harnesses computing power to tackle biological problems. It is particularly essential in the analysis and interpretation of biological data, which have become increasingly complex with advances in genomic and proteomic technologies. Basically, bioinformatics involves the development and application of computer algorithms and statistical methods to understand the biological significance behind data sets.

Arjana’s research focuses on using big data obtained from blood samples and genetic material to identify markers for various diseases. This approach promises to improve our skills in disease prognostication, moving beyond traditional methods based only on symptoms and non-specific laboratory tests. For example, while symptoms such as headaches or blood tests such as glucose levels provide limited diagnostic specificity, bioinformatics can identify certain genetic or molecular markers associated with conditions such as Alzheimer’s, Parkinson’s or cardiovascular diseases.

Finally, Arjana also shared some valuable resources for those coming from a biology/medical background (without computer science background) who want to learn coding for bioinformatics. Here are some recommended sites:

Here are some sites that require more computer science knowledge than biology: