Evidence map›Paper›PMID 31019094›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2019

Network cloning using DNA barcodes.

Sergey A Shuvaev, Batuhan Başerdem, Anthony M Zador, Alexei A Koulakov

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sergey A ShuvaevCold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724.ORCID 0000-0001-5215-8019
Batuhan BaşerdemCold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724.
Anthony M ZadorCold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724.
Alexei A KoulakovCold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724 akula@cshl.edu.

Funding

CRCNS: Theory and experiment of neural circuit mapping by DNA sequencingR01DA036913 · NIDA · COLD SPRING HARBOR LABORATORY · PI KOULAKOV, ALEXEI, ZADOR, ANTHONY M · 2013 to 2017
$2.1M
NIDA NIH HHS R01 DA036913
6 · The paper itself

Abstract

The connections between neurons determine the computations performed by both artificial and biological neural networks. Recently, we have proposed SYNSeq, a method for converting the connectivity of a biological network into a form that can exploit the tremendous efficiencies of high-throughput DNA sequencing. In SYNSeq, each neuron is tagged with a random sequence of DNA-a "barcode"-and synapses are represented as barcode pairs. SYNSeq addresses the analysis problem, reducing a network into a suspension of barcode pairs. Here, we formulate a complementary synthesis problem: How can the suspension of barcode pairs be used to "clone" or copy the network back into an uninitialized tabula rasa network? Although this synthesis problem might be expected to be computationally intractable, we find that, surprisingly, this problem can be solved efficiently, using only neuron-local information. We present the "one-barcode-one-cell" (OBOC) algorithm, which forces all barcodes of a given sequence to coalesce into the same neuron, and show that it converges in a number of steps that is a power law of the network size. Rapid and reliable network cloning with single-synapse precision is thus theoretically possible.

Indexed as

Cloning, MolecularDNA Barcoding, TaxonomicModels, GeneticNeuronsAnimalsHigh-Throughput Nucleotide SequencingHumansSynapsesconnectomicsDNA barcodesneural developmentneural networks

Identifiers

PMID31019094
PMCPMC6511037

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.