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Although the knowledge we have about human cells and tissues has steadily increased over recent decades, many things remain unknown. For instance, cells exist in transient, dynamic states and understanding them is fundamental to decipher diseases and find cures. Classic techniques used in the lab to study cell types faced limitations and did not enable a finely detailed profile of cell function.
To overcome this obstacle, a group of scientists at the National Centre for Genomic Analysis (CNAG-CRG) from the Centre for Genomic Regulation (CRG), in Barcelona, Spain, led by Holger Heyn, developed a new computational tool, based on the mathematical Graph theory, to infer global, large-scale regulatory networks, from healthy and pathological organs, such as those affected by diabetes or Alzheimer's disease. The researchers were able to pinpoint genes relevant to organ function and potential drivers of diseases. They are publishing their results in the current issue of the Genome Biology journal.
Tools - Cell - Types - Giovanni - Iacono
"Our previously developed single-cell transcriptomic tools were very useful to discover unknown cell types," says Giovanni Iacono, senior postdoc researcher at the CNAG-CRG and first author of the study. "Those tools allowed us to describe new types and subtypes of cells, with their unique biological roles and hierarchical relationships," he adds.
Up to now, single-cell analysis had been used to understand cell types and their function within tissue. "Large-scale consortia like the Human Cell Atlas Project generate single-cell maps of entire organisms and sophisticated analysis strategies are required to transform big data into disruptive biological and clinical insights," says Holger Heyn, team leader of the Single Cell...
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