DOI: 10.1016/j.molp.2019.01.
003 link

PMID: 30639314

OpenAlex ID: W2909224061

Category: Biomedical

Title: MapMan4: A Refined Protein Classification and Annotation Framework Applicable to Multi-Omics Data Analysis

Authors: Rainer Schwacke, Marie Bolger, Björn Usadel, Gabriel Yaxal Ponce‐Soto, Kirsten Krause, Anthony Bolger, Borjana Arsova, Asis Hallab, Kristina Gruden,... (10 authors, truncated)

Publishing date: 01-Jun-2019

YCR = 2019  / 338 /  15.40 

Version 1.00            Year       /   Citations  /   Relative

Metric Value Date of Calculation

Citations count

338

30-May-2024

Relative

15.40

04-Aug-2024

Article Expected CPY (Citations per Year): 4.39 Expected CPY Help

Article Actual CPY: 67.60 Actual CPY Help

Article Co-Citation FCR (Field Citation Rate): 5.42 FCR Help

Article Co-Citation Network Size: 30390 Co-Citation Network Size Help

Article Topics: RNA Sequencing Data Analysis, Analysis of Gene Interaction Networks, Prediction of Protein Subcellular Localization Topics help

Article Keywords: genome annotation, Functional Annotations, Genomic Data Integration, Gene Set Enrichment Analysis, Functional Genomics Keywords Help

Journal: Molecular Plant

Journal IF-ycr: 8.846 Journal IF-ycr Help

Journal short code: NA

Journal ISSN: 1674-2052

Journal OA-ID: 150334665

Help

Expected CPY Help: Predicted citations per year for this article, derived from its Field Citation Rate (FCR) using a benchmark regression of NIH-funded papers. Values above actual CPY indicate under-performance; below indicate over-performance. Used as the denominator of the Relative Citation Ratio.

Back to top

Actual CPY Help: Average yearly citations the article has received from publication through the current year, adjusted for partial years. Used as the numerator of the Relative Citation Ratio.

Back to top

FCR Help: Mean journal citation rate for all papers in the article's co-citation network. For each network paper we substitute its journal’s impact factor (calculated from open data) as a proxy for citations per year, then average these values. This captures the citation intensity of the article's immediate research field and forms the basis for computing expected CPY.

Back to top

Co-Citation Network Size Help: Number of unique papers co-cited with this article by its citing papers; larger networks yield more stable field estimates when calculating FCR and expected CPY.

Back to top

Topics Help: OpenAlex assigns topics to each paper with an AI model that considers the title, abstract, journal, and citation links. Tags are chosen from about 4,500 research areas, and the highest-confidence tag becomes the paper's primary topic. Every topic sits in a hierarchy of domain, field, and subfield, so you can see exactly where the work fits in the wider map of science.

Back to top

Keywords Help: Keywords are generated automatically from the paper's assigned topics. The OpenAlex system selects candidate terms, then keeps up to five that match closely with the title or abstract. These keywords highlight specific concepts or methods and give a quick complement to the broader topic tags.

Back to top

Journal IF-ycr Help: Journal IF-ycr is a two-year impact factor recalculated from OpenAlex's open citation data. For a given journal and year Y, we:

  1. Count citations made in year Y by any paper to items that the journal published in years Y-1 and Y-2 (excluding the current year).
  2. Divide that citation count by the number of articles the journal published in those same two years.
This yields an impact factor analogue built entirely from open data, updated annually and used in the YCR workflow.

Back to top