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Claudia Chica

dblp:71/3456 · DBLP profile ↗
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4ranked-venue papers
1as first author
0since 2021 · last 2009
0000-0002-3758-640XORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 4 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence analysis
motif discovery
0.112009
KEPE - a motif frequently superimposed on sumoylation sites in metazoan chromatin proteins and transcription factors · Bioinform. 2009
Bioinformatics and computational biology
sequence analysis
0.112009
KEPE - a motif frequently superimposed on sumoylation sites in metazoan chromatin proteins and transcription factors · Bioinform. 2009
Bioinformatics and computational biology
protein function prediction
0.112008
Discovery of candidate KEN-box motifs using Cell Cycle keyword enrichment combined with native disorder prediction and motif conservation · Bioinform. 2008
Bioinformatics and computational biology › sequence analysis › motif discovery
short linear motif discovery
0.112008
Discovery of candidate KEN-box motifs using Cell Cycle keyword enrichment combined with native disorder prediction and motif conservation · Bioinform. 2008
Bioinformatics and computational biology › protein structure prediction
protein disorder prediction
0.012008
Discovery of candidate KEN-box motifs using Cell Cycle keyword enrichment combined with native disorder prediction and motif conservation · Bioinform. 2008
Bioinformatics and computational biology
protein structure prediction
0.012008
Discovery of candidate KEN-box motifs using Cell Cycle keyword enrichment combined with native disorder prediction and motif conservation · Bioinform. 2008

Methods — techniques the papers use, named apart from their topics

regular expression search · 0.1native disorder prediction · 0.1motif conservation analysis · 0.1keyword enrichment · 0.1
YearPublicationVenuePosition
2009 KEPE - a motif frequently superimposed on sumoylation sites in metazoan chromatin proteins and transcription factors
abstract
MOTIVATION: We noted that the sumoylation site in C/EBP homologues is conserved beyond the canonical consensus sequence for sumoylation. Therefore, we investigated whether this pattern might define a more general protein motif. RESULTS: We undertook a survey of the human proteome using a regular expression based on the C/EBP motif. This revealed significant enrichment of the motif using different Gene Ontology terms (e.g. 'transcription') that pertain to the nucleus. When considering requirements for the motif to be functional (evolutionary conservation, structural accessibility of the motif and proper cell localization of the protein), more than 130 human proteins were retrieved from the UniProt/Swiss-Prot database. These candidates were particularly enriched in transcription factors, including FOS, JUN, Hif-1alpha, MLL2 and members of the KLF, MAF and NFATC families; chromatin modifiers like CHD-8, HDAC4 and DNA Top1; and the transcriptional regulatory kinases HIPK1 and HIPK2. The KEPEmotif appears to be restricted to the metazoan lineage and has three length variants-short, medium and long-which do not appear to interchange.
Francesca Diella, Sophie Chabanis-Davidson, Katja Luck, Claudia Chica, Chenna Ramu, Claus Nerlov, Toby J. Gibson
Bioinform.4
2008 Discovery of candidate KEN-box motifs using Cell Cycle keyword enrichment combined with native disorder prediction and motif conservation
abstract
MOTIVATION: KEN-box-mediated target selection is one of the mechanisms used in the proteasomal destruction of mitotic cell cycle proteins via the APC/C complex. While annotating the Eukaryotic Linear Motif resource (ELM, http://elm.eu.org/), we found that KEN motifs were significantly enriched in human protein entries with cell cycle keywords in the UniProt/Swiss-Prot database-implying that KEN-boxes might be more common than reported. RESULTS: Matches to short linear motifs in protein database searches are not, per se, significant. KEN-box enrichment with cell cycle Gene Ontology terms suggests that collectively these motifs are functional but does not prove that any given instance is so. Candidates were surveyed for native disorder prediction using GlobPlot and IUPred and for motif conservation in homologues. Among >25 strong new candidates, the most notable are human HIPK2, CHFR, CDC27, Dab2, Upf2, kinesin Eg5, DNA Topoisomerase 1 and yeast Cdc5 and Swi5. A similar number of weaker candidates were present. These proteins have yet to be tested for APC/C targeted destruction, providing potential new avenues of research.
Sushama Michael, Gilles Travé, Chenna Ramu, Claudia Chica, Toby J. Gibson
Bioinform.4
2008 A tree-based conservation scoring method for short linear motifs in multiple alignments of protein sequences
abstract
BACKGROUND: The structure of many eukaryotic cell regulatory proteins is highly modular. They are assembled from globular domains, segments of natively disordered polypeptides and short linear motifs. The latter are involved in protein interactions and formation of regulatory complexes. The function of such proteins, which may be difficult to define, is the aggregate of the subfunctions of the modules. It is therefore desirable to efficiently predict linear motifs with some degree of accuracy, yet sequence database searches return results that are not significant. RESULTS: We have developed a method for scoring the conservation of linear motif instances. It requires only primary sequence-derived information (e.g. multiple alignment and sequence tree) and takes into account the degenerate nature of linear motif patterns. On our benchmarking, the method accurately scores 86% of the known positive instances, while distinguishing them from random matches in 78% of the cases. The conservation score is implemented as a real time application designed to be integrated into other tools. It is currently accessible via a Web Service or through a graphical interface. CONCLUSION: The conservation score improves the prediction of linear motifs, by discarding those matches that are unlikely to be functional because they have not been conserved during the evolution of the protein sequences. It is especially useful for instances in non-structured regions of the proteins, where a domain masking filtering strategy is not applicable.
Claudia Chica, Alberto Labarga, Cathryn M. Gould, Rodrigo Lopez, Toby J. Gibson
BMC Bioinform.1
2008 A new protein linear motif benchmark for multiple sequence alignment software
abstract
BACKGROUND: Linear motifs (LMs) are abundant short regulatory sites used for modulating the functions of many eukaryotic proteins. They play important roles in post-translational modification, cell compartment targeting, docking sites for regulatory complex assembly and protein processing and cleavage. Methods for LM detection are now being developed that are strongly dependent on scores for motif conservation in homologous proteins. However, most LMs are found in natively disordered polypeptide segments that evolve rapidly, unhindered by structural constraints on the sequence. These regions of modular proteins are difficult to align using classical multiple sequence alignment programs that are specifically optimised to align the globular domains. As a consequence, poor motif alignment quality is hindering efforts to detect new LMs. RESULTS: We have developed a new benchmark, as part of the BAliBASE suite, designed to assess the ability of standard multiple alignment methods to detect and align LMs. The reference alignments are organised into different test sets representing real alignment problems and contain examples of experimentally verified functional motifs, extracted from the Eukaryotic Linear Motif (ELM) database. The benchmark has been used to evaluate and compare a number of multiple alignment programs. With distantly related proteins, the worst alignment program correctly aligns 48% of LMs compared to 73% for the best program. However, the performance of all the programs is adversely affected by the introduction of other sequences containing false positive motifs. The ranking of the alignment programs based on LM alignment quality is similar to that observed when considering full-length protein alignments, however little correlation was observed between LM and overall alignment quality for individual alignment test cases. CONCLUSION: We have shown that none of the programs currently available is capable of reliably aligning LMs in distantly related sequences and we have highlighted a number of specific problems. The results of the tests suggest possible ways to improve program accuracy for difficult, divergent sequences.
Emmanuel Perrodou, Claudia Chica, Olivier Poch, Toby J. Gibson, Julie Dawn Thompson
BMC Bioinform.2