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An innovative algorithm enables a quantitative comparison of biological processes

Newspaper Nature Methods reports on an innovative algorithm that enables quantitative comparison of biological processes. The algorithm was developed by Associate Professor Shai Shen-Or from the Rappaport Faculty of Medicine at the Technion, who estimates that its applied effects will be broad and significant

The concept behind the new algorithm - the opening of the "black box" called the human immune system. The illustration is courtesy of the Technion.
The concept behind the new algorithm - the opening of the "black box" called the human immune system. The illustration is courtesy of the Technion.

An article published in the journal Nature Methods presents an innovative approach to comparing complex biological processes. The approach was developed by a research group led by Associate Professor Shai Shen-Or, PhD student Ayelet Alpert, Lindsay Moore and Tanya Dubovic from the Rapaport Faculty of Medicine.

In recent years, there has been a leap forward in the development of innovative technologies that collect a lot of information (big data) about individual cells, for example RNA sequencing and mass cytometry. These methods were used to describe developmental processes in a detailed manner and with an unprecedented resolution. However, no suitable quantitative framework has yet been found to compare two processes described in this way.

The innovative algorithm, called cellAlign, makes it possible to utilize the large amount of data obtained by these methods and compare processes in a systematic manner while maintaining high resolution both at the level of time and at the level of the individual gene. According to Prof. Mishna Shen-Or, "the algorithm is able to identify similarities and differences between expression patterns of markers (mRNA or proteins), and this at the highest resolution. Thus, it makes it possible to quantify the level of similarity between the dynamics of genetic pathways in different processes or in different organisms and to identify the evolutionarily conserved dynamics."

Associate Professor Shai Shen-Or. Courtesy of the Technion.
Associate Professor Shai Shen-Or. Courtesy of the Technion.

According to Prof. Mishna Shen-Or, "developments in biological research are largely based on comparisons, and to our knowledge there is no competing method for comparing expression dynamics at such a resolution based on the single cell. It is worth noting that the algorithm is relevant to a wide range of applications in diverse fields, including immunology, developmental and systems biology, and biomedical engineering."

The research group applied the innovative algorithm for the purpose of comparing the genetic expression pathways of genes in the early embryonic stages in humans and mice, an animal that is often used as a model for humans. Using the algorithm, the researchers were able to perform a comparative analysis of genetic pathways on the developmental timeline and determine the activation order of different genes in the process, thus shedding light on similarities and differences between genetic pathways between species.

Using cellAlign, the research group at the Technion was able to identify in human and mouse embryonic development gene groups whose dynamics are evolutionarily conserved. This is in contrast to other groups of genes that are characterized by inhibition in one species compared to the other and those that have completely different dynamics between the species. Since gene dynamics in this early process are critical to the development of the organism, these differences represent physiological changes between species and must be taken into account when drawing biological conclusions from mouse to man.

Doctoral student Ayelet Alpert. Courtesy of the Technion.
Doctoral student Ayelet Alpert. Courtesy of the Technion.

The current article is a breakthrough in the Systems Immunology revolution and the new possibilities it opens up in the world of precision medicine. According to Associate Professor Shen-Or, "Systemic immunology allows us to diagnose the function of the immune system based on biological markers. Through a combination of medical knowledge and computer systems, in the near future we will be able to understand what is happening in the body, when is the right time to give a specific patient a certain drug and how it will affect his immune system. This paradigm will open for us the black box called the human immune system."

For an article in the journal Nature Methods

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