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Adam Spiro
Hebrew University of Jerusalem
Cellular differentiationDNA demethylationDemethylationSpike sortingCluster analysis
4Publications
3H-index
108Citations
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Publications 4
Newest
#1Tal Falick Michaeli (HUJI: Hebrew University of Jerusalem)H-Index: 2
#2Adam Spiro (HUJI: Hebrew University of Jerusalem)H-Index: 3
Last. Yuval Gielchinsky (HUJI: Hebrew University of Jerusalem)H-Index: 10
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#1Yitzhak Reizel (UPenn: University of Pennsylvania)H-Index: 3
#2Ofra Sabag (HUJI: Hebrew University of Jerusalem)H-Index: 7
Last. Howard Cedar (HUJI: Hebrew University of Jerusalem)H-Index: 73
view all 15 authors...
Development in mammals is accompanied by specific de novo and demethylation events that are thought to stabilize differentiated cell phenotypes. We demonstrate that a large percentage of the tissue-specific methylation pattern is generated postnatally. Demethylation in the liver is observed in thousands of enhancer-like sequences associated with genes that undergo activation during the first few weeks of life. Using. conditional gene ablation strategy we show that the removal of these methyl gro...
12 CitationsSource
#1Shari Orlanski (HUJI: Hebrew University of Jerusalem)H-Index: 6
#2Verena LabiH-Index: 21
Last. Yehudit Bergman (HUJI: Hebrew University of Jerusalem)H-Index: 36
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There is ample evidence that somatic cell differentiation during development is accompanied by extensive DNA demethylation of specific sites that vary between cell types. Although the mechanism of this process has not yet been elucidated, it is likely to involve the conversion of 5mC to 5hmC by Tet enzymes. We show that a Tet2/Tet3 conditional knockout at early stages of B-cell development largely prevents lineage-specific programmed demethylation events. This lack of demethylation affects the e...
36 CitationsSource
#1Aharon Bar-Hillel (Interdisciplinary Center for Neural Computation)H-Index: 20
#2Adam Spiro (HUJI: Hebrew University of Jerusalem)H-Index: 3
Last. Eran Stark (HUJI: Hebrew University of Jerusalem)H-Index: 27
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Abstract Spike sorting involves clustering spikes recorded by a micro-electrode according to the source neurons. It is a complicated task, which requires much human labor, in part due to the non-stationary nature of the data. We propose to automate the clustering process in a Bayesian framework, with the source neurons modeled as a non-stationary mixture-of-Gaussians. At a first search stage, the data are divided into short time frames, and candidate descriptions of the data as mixtures-of-Gauss...
58 CitationsSource
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