The immune system is a sensory system, a sixth sense, whose role it is to sense the environment (external or internal) and respond to changes in that environment. Immunity is based on a diffuse system of interacting cells whose net output is greater than the sum of its parts and whose complexity encoded by over a quarter of our genome.
Research in the lab targets three directions:
How the immune system varies over time as a function of environment, particularly with a focus on aging. Our immune system changes a lot, due to all kinds of influences. It starts off being effected predominantly by the genes we inherited. As we get older, our life experiences play a greater and greater role in shaping our immune system. These are all factors and experiences unique to us as individuals. We aim to identify map the possible immune states and the ‘rules of the game’ for how the environmental drivers and molecular mechanisms that transition between states. Our prime focus in this regard is to understand how the healthy immune system changes over life (immune-aging), how these changes in state affect immune response and how they interact with disease.
From identifying immune diagnostics and therapeutic directions to understanding the logistical and cost structure needed to transform healthcare. We can now broadly measure multiple data types on each human blood sample: its immune cell composition; the communication of these cells with one another, and functional tests telling us how a person's immune cells respond to cytokine messages. These technologies give us tremendous power, making it possible to see how everybody’s immune system is a little different and how small differences in biological cell-circuitry ultimately yield clinical differences in outcome. This allows us to develop diagnostics that capture the present status of your disease risk and defenses based not only on your genetics but also on your life history. We focus on developing a clinically relevant metric of immune-aging (IMMAGE) and in understanding the relation of tissue cellular circuitry on clinical responses.
Developing next generation analytical methodologies for grappling with the high complexity of biological and clinical data. We can now generate extremely rich molecular and phenotypic data (i.e. big/deep data) but we can interpret and understand, only a few percent of it. Data growth is exponential whereas insight growth grows linear at best. In short, there is a Data revolution, but we are not getting the bang for the buck from the data generated. We develop computational methods aimed a non-linear increase in insight by tackling fundamental problems in data interpretation. In recent years our focus here has been on enabling the quantitative study of biological process dynamics, especially in the context of inter-cellular communication networks and in tackling the large translational gap that exists between humans and the models used to study humans.
Background: Systems and computational biology, Informatics, Immunology
Why: I am fascinated by how evolution and development forces shape global and emergent properties exhibited by biological systems. Torn between a love of basic science and a commitment to bettering healthcare, I found synergy in Immunology.
How: Imagining a better future, reading between the lines, overcoming obstacles.
Background: Biochemistry and Molecular biology, Immunology
Why: I am a believer in the synergism between experimental and computational biology and that the two combined accelerate our understanding of human biological systems.
How: By development of experimental infrastructure that integrates with computational data. Lab leadership, project management and designing frameworks to study human biology in Israel.
Background: Molecular Genetics, Computational Biology
Why: A passion for mentoring students and blurring the lines between scientific disciplines, and a fascination with systems that change over time (evolution/species, aging, development, language etc.)
How: Teaching data science and computational biology. Lab leadership, project management, algorithmic development.
Background: Economics, Accounting.
Why: I believe that a positive mindset creates a positive environment.
How: Assist with the day-to-day administrative operations in the lab. By working with a great group of people every task is possible.
Background: Human Biology, Biochemistry and Molecular biology
Why: I get a kick from tackling biological problems and seeking answers. I love gaining knowledge and meeting new people.
How: Support many biological projects, each of them is unique and requires a different specialty.
Background: Biotechnology, Biology, Immunology.
Why: I am passionate about biology and immunology in particular. Finding answers to biological questions, learning new techniques, and investigating the immune system fascinates me.
How: Provide support for many areas of biological research using variety of hige dimensional and high throughput single- cell assays.
Background: Systems biologist at heart, trained in cancer biology, yeast genomics and quantitative biology.
Why: Never ceases to be amazed how lifeless molecules come together to form life. The immune system is a formidable use-case for methods tackling emergence.
How: Computational inference of i) cytokine signaling from multi-omic data, ii) immune memory formation and recall from single-cell data and iii) quantitative changes in central dogma components in immune cells during aging.
Background: Biotechnology engineering and neurobiology
Why: Passionate about biology and research from a young age, and more recently, data science and its huge promise to the future.
How: Studying the effects of the baseline state of the immune system (immune-age) on acute responses to perturbations using a mix of lab work and computational approaches.
Background: Electrical engineering
Why: Keen to understand the dynamics that turn a healthy tissue into a sick one.
How: High resolution tissue modeling for spatial ‘omics methods and applications aimed at increasing our understanding of disease progression.
Background: Electrical engineering and data science
Why: Passionate about building advanced methods for solving hard biological (and medical) questions.
How: Focusing on novel methods for fusing knowledge into machine learning pipelines.
Background: Pediatrics (physician at Schneider Children’s Medical Center)
Why: Passionate about understanding/cracking mechanisms of inflammation, to forward true tailored treatment of inflammatory diseases.
How: Utilizing computational and experimental biological models to explore mechanisms of response/non-response to Anti-TNF agents in inflammatory bowel disease.
Background: Pediatric hemato-oncology, bone marrow transplant and immunotherapy speciality.
Why: Fascinated by the revolution of the genomic era bringing it to healthcare.
How: integrate advanced computational analysis with biological research to unravel drivers for accelerating the immune system recovery post chemotherapy treatment.
Background: Pediatric physician and aspiring intensive care clinician.
Why: I am driven to understand why some kids get very sick from simple bugs, and how we can help them heal.
How: Combining clinical experience and passion with biological experimentation and computational analyses I focus on the maturation of the infant immune system and its relationship with viral respiratory diseases causing critical illness.
Why: Driven by the enormous potential of hypothesis-driven data analysis and the impact it could have on patients’ life and well-being.
How: Development of scalable assays to monitor immune aging and its relevance to different clinical conditions, leveraging both molecular and real world data.
Background: Computer Science, Vision and image analysis
Why: Driven by the desire to employ my experience into new and meaningful domains, I returned from industry to academy, replacing Computer Vision with Biology.
How: Computational methods for cross-species translation.
Background: Molecular biochemistry
Why: Driven by the idea that the key to mastering an understanding of the immune system is the combination of clinical, experimental, and computational approaches.
How: Focused on characterizing immune aging in the context of cellular functionality and metabolism with hopes of identifying modulators of aging and improving prognostic abilities.
Background: Computer Science and Bricks and Mortar Architecture. Experience in the MTRL lab.
Why: I glimpse at the miraculous mechanisms of evolution, and I'm inspired to reuse the code, applied to architecture.
How: Pursuing a PhD in the MTRL lab at the Technion, inventing evo-devo architectural algorithms which regulate 3D printed concrete forms.
Background: Computer Science, Bioinformatics
Why: A passion for solving biological challenges from a computational view point.
How: Developing Models and algorithms aimed to acquire a better understanding of biological clocks.
Technion’s Medical School Campus, in Bat Galim, Haifa (5th floor)