Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.

Anna Maria D'Erchia

dblp:30/3301 · DBLP profile ↗
← Back
4ranked-venue papers
0as first author
2since 2021 · last 2021
0000-0002-4627-0626ORCID · reported

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

Applied, interdisciplinary, general and emerging computing · 4 · 2 since 2021

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 · 91% Medical and health informatics · 9%

Topics — the 8 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › genomics
genomic variant analysis
0.512021
VINYL: Variant prIoritizatioN bY survivaL analysis · Bioinform. 2021
Bioinformatics and computational biology › statistical genetics
variant prioritization
0.512021
VINYL: Variant prIoritizatioN bY survivaL analysis · Bioinform. 2021
Medical and health informatics
clinical genomics
0.112021
VINYL: Variant prIoritizatioN bY survivaL analysis · Bioinform. 2021
Bioinformatics and computational biology › genomics
variant annotation
0.112021
VINYL: Variant prIoritizatioN bY survivaL analysis · Bioinform. 2021
Bioinformatics and computational biology › transcriptomics
alternative splicing analysis
0.112008
ASPicDB: A database resource for alternative splicing analysis · Bioinform. 2008
Bioinformatics and computational biology › transcriptomics › transcript isoform analysis
isoform annotation
0.112008
ASPicDB: A database resource for alternative splicing analysis · Bioinform. 2008
Bioinformatics and computational biology › genome annotation
splice site prediction
0.112008
ASPicDB: A database resource for alternative splicing analysis · Bioinform. 2008
Bioinformatics and computational biology › transcriptomics
transcriptome annotation
0.112008
ASPicDB: A database resource for alternative splicing analysis · Bioinform. 2008

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

survival analysis · 0.5functional annotation · 0.5transcript modeling · 0.1multiple sequence alignment · 0.1
YearPublicationVenuePosition
2021 Next generation sequencing of SARS-CoV-2 genomes: challenges, applications and opportunities
abstract
Various next generation sequencing (NGS) based strategies have been successfully used in the recent past for tracing origins and understanding the evolution of infectious agents, investigating the spread and transmission chains of outbreaks, as well as facilitating the development of effective and rapid molecular diagnostic tests and contributing to the hunt for treatments and vaccines. The ongoing COVID-19 pandemic poses one of the greatest global threats in modern history and has already caused severe social and economic costs. The development of efficient and rapid sequencing methods to reconstruct the genomic sequence of SARS-CoV-2, the etiological agent of COVID-19, has been fundamental for the design of diagnostic molecular tests and to devise effective measures and strategies to mitigate the diffusion of the pandemic. Diverse approaches and sequencing methods can, as testified by the number of available sequences, be applied to SARS-CoV-2 genomes. However, each technology and sequencing approach has its own advantages and limitations. In the current review, we will provide a brief, but hopefully comprehensive, account of currently available platforms and methodological approaches for the sequencing of SARS-CoV-2 genomes. We also present an outline of current repositories and databases that provide access to SARS-CoV-2 genomic data and associated metadata. Finally, we offer general advice and guidelines for the appropriate sharing and deposition of SARS-CoV-2 data and metadata, and suggest that more efficient and standardized integration of current and future SARS-CoV-2-related data would greatly facilitate the struggle against this new pathogen. We hope that our 'vademecum' for the production and handling of SARS-CoV-2-related sequencing data, will contribute to this objective.
Matteo Chiara, Anna Maria D'Erchia, Carmela Gissi, Caterina Manzari, Antonio Parisi, Nicoletta Resta, Federico Zambelli, Ernesto Picardi, Giulio Pavesi, David Stephen Horner, Graziano Pesole
Briefings Bioinform.2
2021 VINYL: Variant prIoritizatioN bY survivaL analysis
abstract
MOTIVATION: Clinical applications of genome re-sequencing technologies typically generate large amounts of data that need to be carefully annotated and interpreted to identify genetic variants potentially associated with pathological conditions. In this context, accurate and reproducible methods for the functional annotation and prioritization of genetic variants are of fundamental importance. RESULTS: In this article, we present VINYL, a flexible and fully automated system for the functional annotation and prioritization of genetic variants. Extensive analyses of both real and simulated datasets suggest that VINYL can identify clinically relevant genetic variants in a more accurate manner compared to equivalent state of the art methods, allowing a more rapid and effective prioritization of genetic variants in different experimental settings. As such we believe that VINYL can establish itself as a valuable tool to assist healthcare operators and researchers in clinical genomics investigations. AVAILABILITY AND IMPLEMENTATION: VINYL is available at http://beaconlab.it/VINYL and https://github.com/matteo14c/VINYL. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Matteo Chiara, Pietro Mandreoli, Marco Antonio Tangaro, Anna Maria D'Erchia, Sandro Sorrentino, Cinzia Forleo, David Stephen Horner, Federico Zambelli, Graziano Pesole
Bioinform.4
2008 ASPicDB: A database resource for alternative splicing analysis
abstract
MOTIVATION: Alternative splicing has recently emerged as a key mechanism responsible for the expansion of transcriptome and proteome complexity in human and other organisms. Although several online resources devoted to alternative splicing analysis are available they may suffer from limitations related both to the computational methodologies adopted and to the extent of the annotations they provide that prevent the full exploitation of the available data. Furthermore, current resources provide limited query and download facilities. RESULTS: ASPicDB is a database designed to provide access to reliable annotations of the alternative splicing pattern of human genes and to the functional annotation of predicted splicing isoforms. Splice-site detection and full-length transcript modeling have been carried out by a genome-wide application of the ASPic algorithm, based on the multiple alignments of gene-related transcripts (typically a Unigene cluster) to the genomic sequence, a strategy that greatly improves prediction accuracy compared to methods based on independent and progressive alignments. Enhanced query and download facilities for annotations and sequences allow users to select and extract specific sets of data related to genes, transcripts and introns fulfilling a combination of user-defined criteria. Several tabular and graphical views of the results are presented, providing a comprehensive assessment of the functional implication of alternative splicing in the gene set under investigation. ASPicDB, which is regularly updated on a monthly basis, also includes information on tissue-specific splicing patterns of normal and cancer cells, based on available EST sequences and their library source annotation. AVAILABILITY: www.caspur.it/ASPicDB
Tiziana Castrignanò, Mattia D'Antonio, Anna Anselmo, Danilo Carrabino, A. D'Onorio De Meo, Anna Maria D'Erchia, Flavio Licciulli, Marina Mangiulli, Flavio Mignone, Giulio Pavesi, Ernesto Picardi, Alberto Riva, Raffaella Rizzi, Paola Bonizzoni, Graziano Pesole
Bioinform.6
2007 p53FamTaG: a database resource of human p53, p63 and p73 direct target genes combining in silico prediction and microarray data
abstract
BACKGROUND: The p53 gene family consists of the three genes p53, p63 and p73, which have polyhedral non-overlapping functions in pivotal cellular processes such as DNA synthesis and repair, growth arrest, apoptosis, genome stability, angiogenesis, development and differentiation. These genes encode sequence-specific nuclear transcription factors that recognise the same responsive element (RE) in their target genes. Their inactivation or aberrant expression may determine tumour progression or developmental disease. The discovery of several protein isoforms with antagonistic roles, which are produced by the expression of different promoters and alternative splicing, widened the complexity of the scenario of the transcriptional network of the p53 family members. Therefore, the identification of the genes transactivated by p53 family members is crucial to understand the specific role for each gene in cell cycle regulation. We have combined a genome-wide computational search of p53 family REs and microarray analysis to identify new direct target genes. The huge amount of biological data produced has generated a critical need for bioinformatic tools able to manage and integrate such data and facilitate their retrieval and analysis. DESCRIPTION: We have developed the p53FamTaG database (p53 FAMily TArget Genes), a modular relational database, which contains p53 family direct target genes selected in the human genome searching for the presence of the REs and the expression profile of these target genes obtained by microarray experiments. p53FamTaG database also contains annotations of publicly available databases and links to other experimental data. The genome-wide computational search of the REs was performed using PatSearch, a pattern-matching program implemented in the DNAfan tool. These data were integrated with the microarray results we produced from the overexpression of different isoforms of p53, p63 and p73 stably transfected in isogenic cell lines, allowing the comparative study of the transcriptional activity of all the proteins in the same cellular background.p53FamTaG database is available free at http://www2.ba.itb.cnr.it/p53FamTaG/ CONCLUSION: p53FamTaG represents a unique integrated resource of human direct p53 family target genes that is extensively annotated and provides the users with an efficient query/retrieval system which displays the results of our microarray experiments and allows the export of RE sequences. The database was developed for supporting and integrating high-throughput in silico and experimental analyses and represents an important reference source of knowledge for research groups involved in the field of oncogenesis, apoptosis and cell cycle regulation.
Elisabetta Sbisà, Domenico Catalano, Giorgio Grillo, Flavio Licciulli, Antonio Turi, Sabino Liuni, Graziano Pesole, Anna De Grassi, Mariano Francesco Caratozzolo, Anna Maria D'Erchia, Beatriz Navarro, Apollonia Tullo, Cecilia Saccone, Andreas Gisel
BMC Bioinform.10