Evidence map›Paper›PMID 40728617›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

Comprehensive Prediction of Protein Localization and Signal Peptides Using MULocDeep.

Lei Jiang, Weinan Zhang, Shuai Zeng, Yuexu Jiang, Dong Xu

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. 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

5 authors.

Lei JiangDepartment of Electrical Engineering and Computer Science, Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA.
Weinan ZhangDepartment of Electrical Engineering and Computer Science, Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA.
Shuai ZengDepartment of Electrical Engineering and Computer Science, Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA.
Yuexu JiangDepartment of Electrical Engineering and Computer Science, Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA.
Dong XuDepartment of Electrical Engineering and Computer Science, Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA. xudong@missouri.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Localization of a protein within a cell encompasses various processes and signaling events, including guidance of signal peptides. Accurate prediction of subcellular and suborganellar protein localization, as well as signal peptides, is crucial for understanding protein function and provides valuable insights into cellular mechanisms. Although many computational methods can predict either general protein localization, suborganellar localization, or signal peptides, the lack of comprehensive and intuitive interpretation, insufficient coverage of localization types, and issues related to ease of use are some common limitations. In this chapter, we introduce MULocDeep, an advanced web server designed for the prediction of protein localization at both subcellular and suborganellar levels, as well as the identification of signal peptides and their corresponding cleavage sites. This web server integrates a sophisticated protein large language model, enabling highly accurate predictions and facilitating the interpretation of results. The server also includes multiple interactive interfaces that enhance the clarity and accessibility of predictions, particularly concerning motif patterns within protein sequences. Furthermore, we demonstrate the practical functionality of the MULocDeep web server, providing detailed instructions on how to utilize the server and interpret the results for both localization and signal peptide prediction. The MULocDeep web server is publicly available at https://www.mu-loc.org/ .

Indexed as

Computational BiologyProteinsProtein Sorting SignalsSoftwareDatabases, ProteinHumansInternetProtein TransportProteinsProtein Sorting SignalsCleavage siteDeep learningProtein large language modelProtein localizationSignal peptideSubcellularSuborganellarWeb server

Identifiers

What Socratic 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 Socratic graph.