The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Composition Profiler: a tool for discovery and visualization of amino acid composition differences
Open accessAbstract
Background: Composition Profiler is a web-based tool for semi-automatic discovery of enrichment or depletion of amino acids, either individually or grouped by their physico-chemical or structural properties. Results: The program takes two samples of amino acids as input: a query sample and a reference sample. The latter provides a suitable background amino acid distribution, and should be chosen according to the nature of the query sample, for example, a standard protein database (e.g. SwissProt, PDB), a representative sample of proteins from the organism under study, or a group of proteins with a contrasting functional annotation. The results of the analysis of amino acid composition differences are summarized in textual and graphical form. Conclusion: As an exploratory data mining tool, our software can be used to guide feature selection for protein function or structure predictors. For classes of proteins with significant differences in frequencies of amino acids having particular physico-chemical (e.g. hydrophobicity or charge) or structural (e.g. α helix propensity) properties, Composition Profiler can be used as a rough, light-weight visual classifier.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Berman, H. M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.235 · Cited by 40,196
A simple method for displaying the hydropathic character of a protein
Kyte, J., & Doolittle, R. F. (1982) · Journal of Molecular Biology · doi:10.1016/0022-2836(82)90515-0 · Cited by 22,843
The Universal Protein Resource (UniProt)
Bairoch, A. (2004) · Nucleic Acids Research · doi:10.1093/nar/gki070 · Cited by 3,774
Principles of protein-protein interactions
Jones, S., & Thornton, J. M. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.1.13 · Cited by 2,684
Analysis of membrane and surface protein sequences with the hydrophobic moment plot
Eisenberg, D., Schwarz, E., Komaromy, M., & Wall, R. (1984) · Journal of Molecular Biology · doi:10.1016/0022-2836(84)90309-7 · Cited by 2,284
Intrinsically disordered protein
Dunker, A. K., Lawson, J. D., Brown, C. J., Williams, R. M., Romero, P., Oh, J. S., Oldfield, C. J., Campen, A. M., Ratliff, C. M., Hipps, K. W., et al. (2001) · Journal of Molecular Graphics and Modelling · doi:10.1016/s1093-3263(00)00138-8 · Cited by 2,272
Self-citationSequence complexity of disordered protein
Romero, P., Obradovic, Z., Li, X., Garner, E. C., Brown, C. J., & Dunker, A. K. (2001) · Proteins: Structure, Function, and Genetics · doi:10.1002/1097-0134(20010101)42:1<38::aid-prot50>3.0.co;2-3 · Cited by 1,786
Self-citationIntrinsically Disordered Proteins
Uversky, V. N. (2013) · Brenner's Encyclopedia of Genetics · doi:10.1016/b978-0-12-374984-0.01698-3 · Cited by 1,637
Self-citationIntrinsic Disorder in Cell-signaling and Cancer-associated Proteins
Iakoucheva, L. M., Brown, C. J., Lawson, J. D., Obradović, Z., & Dunker, A. K. (2002) · Journal of Molecular Biology · doi:10.1016/s0022-2836(02)00969-5 · Cited by 1,214
Self-citationDisProt: the Database of Disordered Proteins
Sickmeier, M., Hamilton, J. A., LeGall, T., Vacic, V., Cortese, M. S., Tantos, A., Szabo, B., Tompa, P., Chen, J., Uversky, V. N., et al. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkl893 · Cited by 797
Self-citation
Cited by
Intrinsically Disordered Proteins and Intrinsically Disordered Protein Regions
Oldfield, C. J., & Dunker, A. K. (2014) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-072711-164947 · Cited by 1,057
Self-citationUnusual biophysics of intrinsically disordered proteins
Uversky, V. N. (2013) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2012.12.008 · Cited by 566
Self-citationIntrinsically Disordered Proteins and Their “Mysterious” (Meta)Physics
Uversky, V. N. (2019) · Frontiers in Physics · doi:10.3389/fphy.2019.00010 · Cited by 532
Self-citationIntrinsically disordered proteins from A to Z
Uversky, V. N. (2011) · The International Journal of Biochemistry & Cell Biology · doi:10.1016/j.biocel.2011.04.001 · Cited by 440
Self-citationPredicting intrinsic disorder in proteins: an overview
He, B., Wang, K., Liu, Y., Xue, B., Uversky, V. N., & Dunker, A. K. (2009) · Cell Research · doi:10.1038/cr.2009.87 · Cited by 425
Self-citation
Metadata
- Authors
- Vacic, V., Uversky, V. N., Dunker, A. K., & Lonardi, S.
- Venue
- BMC Bioinformatics
- Published
- 2007-06-19
- Volume
- 8
- Issue
- 1
- Pages
- 211-211
- ISSN
- 1471-2105 (ISSN-L)
- OpenAlex
- W2009815491
- Cited by
- 428
- References
- 20
- FWCI
- 4.43
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Composition Profiler: a tool for discovery and visualization of amino acid composition differences. https://app.cochat.ai/papers/10.1186/1471-2105-8-211
- The paper
- Vacic, V., Uversky, V. N., Dunker, A. K., & Lonardi, S. (2007). Composition Profiler: a tool for discovery and visualization of amino acid composition differences. BMC Bioinformatics. https://doi.org/10.1186/1471-2105-8-211
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
