Starts 30 Jun 2023 11:00
Ends 30 Jun 2023 12:00
Central European Time
QLS Seminar: Computational genomics and dark DNA: data types, approaches, methods
ICTP
Leonardo Building - Luigi Stasi Seminar Room
Abstract:
Computational genomics is a field of research that utilizes robust computational and statistical approaches to decode the functional information hidden in genomic and transcriptomic sequences. Drastically lowered sequencing costs have resulted in accumulation of massive amounts of genomic datasets with estimates that predict that genomics research will generate between 2 and 40 exabytes of data within this decade. Our ability to fully decipher knowledge that sequencing datasets contain is far behind the advancements of sequencing techniques. This makes computational genomics a vibrant field of research for the foreseeable future.
As is well-known, DNA provides the necessary instructions for the creation and maintenance of the proteins responsible for constructing and supporting our bodies. Historically, most of the effort was focused on studying this protein-coding part of the genome. However, only about 2% of our DNA encodes proteins. The remaining 98% is non-coding DNA which was long regarded as “junk” DNA. Over time, scientific studies have revealed the significant role of non-coding DNA in both biological processes and the process of evolution.
In the first part of the talk, I will give an introduction to the field of computational genomics highlighting the most common approaches and data types. In the second part, I will focus on the “dark” DNA, namely on transposable elements: mobile genetic elements that are able to self-propagate, and represent almost half of the human genome. I will show by several examples how computational approaches can facilitate scientific discovery in biology.
Computational genomics is a field of research that utilizes robust computational and statistical approaches to decode the functional information hidden in genomic and transcriptomic sequences. Drastically lowered sequencing costs have resulted in accumulation of massive amounts of genomic datasets with estimates that predict that genomics research will generate between 2 and 40 exabytes of data within this decade. Our ability to fully decipher knowledge that sequencing datasets contain is far behind the advancements of sequencing techniques. This makes computational genomics a vibrant field of research for the foreseeable future.
As is well-known, DNA provides the necessary instructions for the creation and maintenance of the proteins responsible for constructing and supporting our bodies. Historically, most of the effort was focused on studying this protein-coding part of the genome. However, only about 2% of our DNA encodes proteins. The remaining 98% is non-coding DNA which was long regarded as “junk” DNA. Over time, scientific studies have revealed the significant role of non-coding DNA in both biological processes and the process of evolution.
In the first part of the talk, I will give an introduction to the field of computational genomics highlighting the most common approaches and data types. In the second part, I will focus on the “dark” DNA, namely on transposable elements: mobile genetic elements that are able to self-propagate, and represent almost half of the human genome. I will show by several examples how computational approaches can facilitate scientific discovery in biology.