ArticleGenes2023
Improving the Completeness of Chromosome-Level Assembly by Recalling Sequences from Lost Contigs.
Article in Genes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- From genomes to interventions: computational strategies transforming parasitology.Frontiers in veterinary science · 2026Review
- A metagenomic approach to demystify the anaerobic digestion black box and achieve higher biogas yield: a review.Frontiers in microbiology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
For a long time, the construction of complete reference genomes for complex eukaryotic genomes has been hindered by the limitations of sequencing technologies. Recently, the Pacific Biosciences (PacBio) HiFi data and Oxford Nanopore Technologies (ONT) Ultra-Long data, leveraging their respective advantages in accuracy and length, have provided an opportunity for generating complete chromosome sequences. Nevertheless, for the majority of genomes, the chromosome-level assemblies generated using existing methods still miss a high proportion of sequences due to losing small contigs in the step of assembly and scaffolding. To address this shortcoming, in this paper, we propose a novel method that is able to identify and fill the gaps in the chromosome-level assembly by recalling the sequences in the lost small contigs. Experimental results on both real and simulated datasets demonstrate that this method is able to improve the completeness of the chromosome-level assembly.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.