BIGL

The focus of the BioInformatics and Genomic Privacy Laboratory (BIGL) is to study privacy issues associated with DNA sequencing. The head of the lab is Ninoslav Marina, PhD.

The main topic of BIGL is to study methods and develop algorithms and tools for storing, retrieving, organizing and analyzing biological data.

Image and signal processing algorithms provide useful results from large amounts of raw data. In the field of genetics and genomics, we aim at sequencing and annotating genomes and their observed mutations, as well as analyzing gene and protein expression and regulation. Our tools help the simulation and modeling of DNA, RNA, and protein structures as well as molecular interactions.

The methods used in our group include information theory, probability theory and statistics, stochastic modeling, image and signal processing, discrete mathematics, control theory, and data mining.

As these days, the whole genome sequencing becomes easier than ever and extracting the genomic data becomes faster and less complex, genomic privacy of individuals becomes more vulnerable and harder to protect. The main focus of BIGL is to study and design models and algorithms that protect the genomic data by using the most fundamental form of data protection known today: information-theoretic (I-T) security. It follows Kerckhoffs’s principle : A cryptosystem should be secure even if everything about the system, except the key, is public knowledge. A cryptosystem is information-theoretically secure even when the adversary has unlimited computing power and does know the secret codebook. Information theory offers tools to design codes that maximize the useful communication rate while minimizing the “leak” rate of confidential information to unwanted parties. The efficiency of an algorithm that provides information-theoretic security does not depend on the computational power of the attacker and is not vulnerable to future developments. I-T secure cryptosystems have been used for the most sensitive governmental communications, such as diplomatic cables and high-level military communications. We use this fundamental knowledge to ensure privacy and anonymity for subjects that got their DNA sampled and sequenced. Exposure to the DNA data can lead not only to a serious threat to one’s privacy but also to the privacy of her ancestors, descendants and relatives. Hence, we believe that unconditional security based on information theory is a fundamental way for data protection in general, and since the data related to the DNA is both big and sensitive, I-T secrecy may offer elegant practically implementable long-term solutions. This project will provide a unique expertise to a totally new and important area as the genomic privacy, making it original, ground-breaking and multidisciplinary.