Evidence map›Paper›PMID 32402076›Full record

ArticleNucleic acids research2020

InteractomeSeq: a web server for the identification and profiling of domains and epitopes from phage display and next generation sequencing data.

Simone Puccio, Giorgio Grillo, Arianna Consiglio, Maria Felicia Soluri, Daniele Sblattero, Diego Cotella, Claudio Santoro, Sabino Liuni, Gianluca De Bellis, Enrico Lugli and 2 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Defining theFrontiers in microbiology · 2020
    Article
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

12 authors.

Simone PuccioLaboratory of Translational Immunology, Humanitas Clinical and Research Center, IRCCS, Rozzano (Milan), 20089, Italy.
Giorgio GrilloInstitute for Biomedical Technologies, National Research Council, Bari 70100, Italy.
Arianna ConsiglioInstitute for Biomedical Technologies, National Research Council, Bari 70100, Italy.
Maria Felicia SoluriDepartment of Health Sciences & Center for TranslationalResearch on Autoimmune and Allergic Disease (CAAD), Università del Piemonte Orientale, Novara 28100, Italy.
Daniele SblatteroDepartment of Life Sciences, University of Trieste, Trieste 34100, Italy.
Diego CotellaDepartment of Health Sciences & Center for TranslationalResearch on Autoimmune and Allergic Disease (CAAD), Università del Piemonte Orientale, Novara 28100, Italy.
Claudio SantoroDepartment of Health Sciences & Center for TranslationalResearch on Autoimmune and Allergic Disease (CAAD), Università del Piemonte Orientale, Novara 28100, Italy.
Sabino LiuniInstitute for Biomedical Technologies, National Research Council, Bari 70100, Italy.
Gianluca De BellisInstitute for Biomedical Technologies, National Research Council, Segrate (Milan) 20090, Italy.
Enrico LugliLaboratory of Translational Immunology, Humanitas Clinical and Research Center, IRCCS, Rozzano (Milan), 20089, Italy.
Clelia PeanoInstitute of Genetic and Biomedical Research, UoS Milan, National Research Council, Rozzano (Milan) 20089, Italy.
Flavio LicciulliInstitute for Biomedical Technologies, National Research Council, Bari 70100, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-Throughput Sequencing technologies are transforming many research fields, including the analysis of phage display libraries. The phage display technology coupled with deep sequencing was introduced more than a decade ago and holds the potential to circumvent the traditional laborious picking and testing of individual phage rescued clones. However, from a bioinformatics point of view, the analysis of this kind of data was always performed by adapting tools designed for other purposes, thus not considering the noise background typical of the 'interactome sequencing' approach and the heterogeneity of the data. InteractomeSeq is a web server allowing data analysis of protein domains ('domainome') or epitopes ('epitome') from either Eukaryotic or Prokaryotic genomic phage libraries generated and selected by following an Interactome sequencing approach. InteractomeSeq allows users to upload raw sequencing data and to obtain an accurate characterization of domainome/epitome profiles after setting the parameters required to tune the analysis. The release of this tool is relevant for the scientific and clinical community, because InteractomeSeq will fill an existing gap in the field of large-scale biomarkers profiling, reverse vaccinology, and structural/functional studies, thus contributing essential information for gene annotation or antigen identification. InteractomeSeq is freely available at https://InteractomeSeq.ba.itb.cnr.it/.

Indexed as

Cell Surface Display TechniquesEpitopesHigh-Throughput Nucleotide SequencingProtein DomainsSoftwareBacteriophagesInternetEpitopes

Identifiers

PMID32402076
PMCPMC7319578

What OpenQuestion holds

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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.