Welcome to the website of the Computational Biology Lab

About our research

Computational Neuroscience Projects

We are interested in understanding how dendrites and their integrative properties contribute to learning and memory functions. Towards this goal, we build abstract mathematical as well as detailed biophysical models of neural cells and circuits across multiple brain regions (hippocampus, amygdala, PFC) and abstraction levels (single neurons, microcircuits, neuronal networks). We then use the models to study how the anatomical, biophysical and plasticity properties of dendrites contribute to memory functions.


Bioinformatics Projects

We focus on developing computational methods and tools for (a) analyzing large-scale gene expression data related to human cancer in search for gene markers and disease sub-categories, (b) identifying regulatory elements such as miRNA precursors and their targets in whole genomes of plants and mammals, (c) building theoretical models of gene regulatory networks. Our methodological approaches include (a) novel clustering and feature selection algorithms, (b) machine learning algorithms such as artificial neural networks, hidden Markov models etc.



WEF ERC IdeasLab 2014




Latest News

Alexandra Tzilivaki was selected as Next Generation Woman Leader by McKinsey and Company

Our lab member Alexandra Tzilivaki, PhD candidate at Charite Medical School Berlin and IMBB FORTH, was recently appointed as Next Generation Woman Leader by McKinsey & Company.


Dr. Papoutsi, along with Dr. Mari, receive the highly competitive ELIDEK (HFRI) grant

The young investigators will benefit from the ELIDEK (HFRI) financial support to establish novel and multi-disciplinary neuroscience research at our host institute, IMBB-FORTH.


Our publication in Nature Communications is recommended by F1000 for its special significance in the field

"This study is remarkable in that it links microscale remodeling of dendritic spine architecture to behavioral performance in adult mice, outside of the developmentally relevant critical period. The results pave the way for interesting future questions to address ..."

Access the recommendation on F1000Prime


IMBB and UCLA researchers show how synaptic turnover facilitates learning and memory

The laboratory of Dr. Alcino Silva at the University of California Los Angeles joined forces with the lab of Dr. Poirazi at IMBB-FORTH in order to explain why the "banding together" of synapses in dendrites relates to better learning and memory. The work is published in the scientific journal Nature Communications, and is likely to have important implications for memory-related dysfunctions. 

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