Evidence map›Paper›PMID 38496496›Full record

ArticlebioRxiv : the preprint server for biology2024

Maximum Likelihood Inference of Time-scaled Cell Lineage Trees with Mixed-type Missing Data.

Uyen Mai, Gillian Chu, Benjamin J Raphael

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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

5 · Who and what money

Authors and funding

3 authors.

Uyen MaiDepartment of Computer Science, Princeton University, Princeton, NJ 08544, USA.ORCID 0000-0001-5065-2814
Gillian ChuDepartment of Computer Science, Princeton University, Princeton, NJ 08544, USA.ORCID 0000-0003-2205-730X
Benjamin J RaphaelDepartment of Computer Science, Princeton University, Princeton, NJ 08544, USA.ORCID 0000-0003-1274-048X

Funding

Comprehensive and Robust Tools for Analysis of Tumor Heterogeneity and EvolutionU24CA248453 · NCI · PRINCETON UNIVERSITY · PI Benjamin Raphael · 2020 to 2026
$4.7M
NCI NIH HHS U24 CA248453
6 · The paper itself

Abstract

Recent dynamic lineage tracing technologies combine CRISPR-based genome editing with single-cell sequencing to track cell divisions during development. A key computational problem in dynamic lineage tracing is to infer a cell lineage tree from the measured CRISPR-induced mutations. Three features of dynamic lineage tracing data distinguish this problem from standard phylogenetic tree inference. First, the CRISPR-editing process modifies a genomic location exactly once. This

Identifiers

PMID38496496
PMCPMC10942411

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.