Evidence map›Paper›PMID 42681321›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

isoTar: miRNA-Target Consensus Prediction with Enrichment Analysis for Canonical and Modified miRNAs.

Sebastiano Di Bella, Francesco Orilio, Shaopeng Gu, Rosario Distefano, Junhao Liu, Miriam Gaggianesi, Rosario Nicola Brancaccio, Shaohong Feng, Alessandro Laganà, Mario Acunzo and 2 more

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2026. 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

12 authors.

Sebastiano Di Bella *Department of Precision Medicine in Medical, Surgical and Critical Care, University of Palermo, Palermo, Italy.
Francesco Orilio *Department of Precision Medicine in Medical, Surgical and Critical Care, University of Palermo, Palermo, Italy.
Shaopeng GuDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.
Rosario DistefanoDivision of Hematology, Department of Internal Medicine, The Ohio State University, Columbus, OH, USA.
Junhao LiuComputer Science and Engineering, College of Engineering, The Ohio State University, Columbus, OH, USA.
Miriam GaggianesiDepartment of Precision Medicine in Medical, Surgical and Critical Care, University of Palermo, Palermo, Italy.
Rosario Nicola BrancaccioDepartment of Precision Medicine in Medical, Surgical and Critical Care, University of Palermo, Palermo, Italy.
Shaohong FengDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.
Alessandro LaganàThe Tisch Cancer Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Mario AcunzoDepartment of Medicine and Surgery, LUM "Giuseppe Degennaro", Casamassima, Bari, Italy.
Qin MaDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.
Giovanni NigitaPelotonia Institute for Immuno-Oncology, The Arthur G. James Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. giovanni.nigita@osumc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the past few decades, microRNAs (miRNAs) have gained significant attention for their role in regulating gene expression and their association with various diseases, including cancer. These small noncoding RNAs (sncRNAs) have been identified as crucial regulators of different biological functions. However, recent advancements in high-throughput sequencing technologies have revealed a more complex miRNAome, driven by phenomena such as RNA editing and isomiRs, which modify miRNA sequences. This increasing complexity has necessitated the development of new tools to analyze the miRNAome and better understand their biological roles. To address this challenge, isoTar was developed-a high-performance, web-based containerized application designed for miRNA consensus-targeting prediction and functional enrichment analyses. This chapter provides a comprehensive overview of isoTar ( https://ncrnaome.osumc.edu/isotar/ ), including benchmarks of its performance and a guide to its usage.

Indexed as

Computational BiologyMicroRNAsSoftwareHigh-Throughput Nucleotide SequencingHumansRNA EditingSequence Analysis, RNAMicroRNAsA-to-I RNA editingConsensus predictionFunctional enrichment analysisisomiRsMicroRNA target prediction

Identifiers

PMID42681321

What OpenQuestion holds

Textmetadata
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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.