Evidence map›Paper›PMID 31628256›Full record

ArticleGenome research2019

PhISCS: a combinatorial approach for subperfect tumor phylogeny reconstruction via integrative use of single-cell and bulk sequencing data.

Salem Malikic, Farid Rashidi Mehrabadi, Simone Ciccolella, Md Khaledur Rahman, Camir Ricketts, Ehsan Haghshenas, Daniel Seidman, Faraz Hach, Iman Hajirasouliha, S Cenk Sahinalp

Abstract read
In one paragraph

Article in Genome research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing 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

46 citing papers in PubMed.

  1. Article
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  4. Sc-TUSV-Ext: Single-Cell Clonal Lineage Inference from Single Nucleotide Variants, Copy Number Alterations, and Structural Variants.Journal of computational biology : a journal of computational molecular cell biology · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Resolving tumor evolution: a phylogenetic approach.Journal of the National Cancer Center · 2024
    Review
  9. Article
  10. Predicting horizontal gene transfers with perfect transfer networks.Algorithms for molecular biology : AMB · 2024
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
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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

10 authors.

Salem MalikicSchool of Computing Science, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.
Farid Rashidi MehrabadiDepartment of Computer Science, Indiana University, Bloomington, Indiana 47408, USA.
Simone CiccolellaDepartment of Computer Systems and Communication, University of Milano-Bicocca, 20136 Milan, Italy.
Md Khaledur RahmanDepartment of Computer Science, Indiana University, Bloomington, Indiana 47408, USA.
Camir RickettsInstitute for Computational Biomedicine, Weill Cornell Medicine, New York, New York 10065, USA.
Ehsan HaghshenasSchool of Computing Science, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.
Daniel SeidmanTri-I Computational Biology and Medicine Graduate Program, Cornell University, New York, New York 10065, USA.
Faraz HachSchool of Computing Science, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.
Iman HajirasoulihaInstitute for Computational Biomedicine, Weill Cornell Medicine, New York, New York 10065, USA.
S Cenk SahinalpCancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.

Funding

Tri-Institutional Training Program in Computational Biology & MedicineT32GM083937 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI CHRISTINI, DAVID J. · 2009 to 2018
$3.1M
NIGMS NIH HHS T32 GM083937
6 · The paper itself

Abstract

Available computational methods for tumor phylogeny inference via single-cell sequencing (SCS) data typically aim to identify the most likely

Indexed as

PhylogenyComputational BiologyHigh-Throughput Nucleotide SequencingHumansNeoplasmsSingle-Cell Analysis

Identifiers

PMID31628256
PMCPMC6836735

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.