
My father-in-law, Abraham Colton,
passed away at age 77 from Lymphoma cancer
Recent technological developments in generating biological data, such as next-generation DNA/RNA sequencing, has led to an exponential growth of biological data. This is particularly true of cancer data, as DNA sequencing is a routine procedure at many medical centers. The main bottleneck for research is therefore not in data generation but rather in interpreting this wealth of data. In our lab, we develop new algorithms and computational tools for analyzing cancer data, and apply them to the abundance of newly available data, with the goal of generating new biological insights and medical diagnostic tools.
While our interest spans all aspects of cancer bioinformatics, our current main focus is on the genomics of tumors that develop due to a deficiency in one of the DNA repair pathways.
As examples, two of the lab’s current projects include:
My research is based on the assumption that random mutations arising during DNA replication in normal, noncancerous stem cells may contribute to cancer development. Therefore, estimating the mutation-rate in which an individual accumulates mutations can help to predict cancer development for each individual, as well as predict characteristics of the emergence of drug resistance for each individual and each drug. Currently, my research is focused on locating common genetic variations that contribute to the development of colon cancer.
The subject of my research is Polygenic Risk Scores (PRS) for predicting the risk of colon cancer. What is PRS? Until today, the world of medicine could divide people into different risk groups using screening tests outcomes and using classic risk factors, such as age, smoking status, and family history. With the development of genetic knowledge and techniques, we might add personal genetic data to this risk calculation. Using a simple blood test, we can learn about the genetic code of a person. Our mission is to predict cancer risk using a unique score called PRS. PRS means Polygenic Risk Scores, and it is comprised of classic risk factors and genetic data as well. PRS prediction would be executed using bioinformatics methods.
- B.Sc. in Biotechnology and Food Engineering from the Technion- Israel Institute of Technology (2020).
- Joined the team on March 2020.
Characterization of cancer by using ensemble learning algorithms.
I have just received my B.Sc in material engineering and physics.
I am developing computational tools that can detect cancerous DNA in the cell free DNA. These tools can be used for early detection.
I am interested in the development of efficient algorithms and heuristics to model and analyze biological systems.
Currently, my research is focused on developing computational tools to deduce molecular characteristics of tumors from imaging and sequencing data
We have a few open positions for postdoc and Ph.D. and masters students in the wide field of cancer bioinformatics.
Curious and motivated people can apply for these positions.
All relevant backgrounds are welcome, which can range from mathematics and computer science to biology and medicine, including also physics and engineering or any other relevant training.
The most important quality we are looking for is an eagerness to learn new fields and to dive into new topics.
Please contact us at [email protected]
My father-in-law, Abraham Colton,
passed away at age 77 from Lymphoma cancer
My cousin, Dov (Irad) Eisenbach,
passed away at age 33 from tongue cancer.
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