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Angel Pizarro

Publications and source records attributed to Angel Pizarro.

9 recordsLinked to original sources
PubMed2006

EBP, a program for protein identification using multiple tandem mass spectrometry datasets.

MS/MS combined with database search methods can identify the proteins present in complex mixtures. High throughput methods that infer probable peptide sequences from enzymatically digested protein samples create a challenge in how best to aggregate the evidence for candidate proteins. Typically the results of multiple technical and/or biological replicate experiments must be combined to maximize sensitivity. We present a statistical method for estimating probabilities of protein expression that integrates peptide sequence identifications from multiple search algorithms and replicate experimental runs. The method was applied to create a repository of 797 non-homologous zebrafish (Danio rerio) proteins, at an empirically validated false identification rate under 1%, as a resource for the development of targeted quantitative proteomics assays. We have implemented this statistical method as an analytic module that can be integrated with an existing suite of open-source proteomics software.

Algorithms↗
PubMed2006

Proteomics and Beyond: a report on the 3rd Annual Spring Workshop of the HUPO-PSI 21-23 April 2006, San Francisco, CA, USA.

The theme of the third annual Spring workshop of the HUPO-PSI was "proteomics and beyond" and its underlying goal was to reach beyond the boundaries of the proteomics community to interact with groups working on the similar issues of developing interchange standards and minimal reporting requirements. Significant developments in many of the HUPO-PSI XML interchange formats, minimal reporting requirements and accompanying controlled vocabularies were reported, with many of these now feeding into the broader efforts of the Functional Genomics Experiment (FuGE) data model and Functional Genomics Ontology (FuGO) ontologies.

Animals↗
PubMed2006

FuGE: Functional Genomics Experiment Object Model.

This is an interim report on the Functional Genomics Experiment (FuGE) Object Model. FuGE is a framework for creating data standards for high-throughput biological experiments, developed by a consortium of researchers from academia and industry. FuGE supports rich annotation of samples, protocols, instruments, and software, as well as providing extension points for technology specific details. It has been adopted by microarray and proteomics standards bodies as a basis for forthcoming standards. It is hoped that standards developers for other omics techniques will join this collaborative effort; widespread adoption will allow uniform annotation of common parts of functional genomics workflows, reduce standard development and learning times through the sharing of consistent practice, and ease the construction of software for accessing and integrating functional genomics data.

Computer Simulation↗
PubMed2005

[Topical treatment of melanoma skin metastases with imiquimod].

The treatment of skin metastases of melanoma can be difficult in many cases because of the patients age, as well as the number, size and location of the lesions. We present the case of an 82-year-old male with melanoma skin metastases on the scalp, which responded satisfactorily to treatment with 5 % imiquimod cream. Imiquimod is a topical immunomodulator with antiviral and antineoplastic action. This case, along with others that have recently been published, supports the usefulness of this treatment in selected cases of melanoma skin metastases, at least for palliative purposes.

Administration, Topical↗
PubMed2004

An object model and database for functional genomics.

MOTIVATION: Large-scale functional genomics analysis is now feasible and presents significant challenges in data analysis, storage and querying. Data standards are required to enable the development of public data repositories and to improve data sharing. There is an established data format for microarrays (microarray gene expression markup language, MAGE-ML) and a draft standard for proteomics (PEDRo). We believe that all types of functional genomics experiments should be annotated in a consistent manner, and we hope to open up new ways of comparing multiple datasets used in functional genomics. RESULTS: We have created a functional genomics experiment object model (FGE-OM), developed from the microarray model, MAGE-OM and two models for proteomics, PEDRo and our own model (Gla-PSI-Glasgow Proposal for the Proteomics Standards Initiative). FGE-OM comprises three namespaces representing (i) the parts of the model common to all functional genomics experiments; (ii) microarray-specific components; and (iii) proteomics-specific components. We believe that FGE-OM should initiate discussion about the contents and structure of the next version of MAGE and the future of proteomics standards. A prototype database called RNA And Protein Abundance Database (RAPAD), based on FGE-OM, has been implemented and populated with data from microbial pathogenesis. AVAILABILITY: FGE-OM and the RAPAD schema are available from http://www.gusdb.org/fge.html, along with a set of more detailed diagrams. RAPAD can be accessed by registration at the site.

Abstracting and Indexing↗
PubMed2003

Transcriptional program of the endocrine pancreas in mice and humans.

The Endocrine Pancreas Consortium was formed in late 1999 to derive and sequence cDNA libraries enriched for rare transcripts expressed in the mammalian endocrine pancreas. Over the past 3 years, the Consortium has generated 20 cDNA libraries from mouse and human pancreatic tissues and deposited >150,000 sequences into the public expressed sequence tag databases. A special effort was made to enrich for cDNAs from the endocrine pancreas by constructing libraries from isolated islets. In addition, we constructed a library in which fetal pancreas from Neurogenin 3 null mice, which consists of only exocrine and duct cells, was subtracted from fetal wild-type pancreas to enrich for the transcripts from the endocrine compartment. Sequence analysis showed that these clones cluster into 9,464 assembly groups (approximating unique transcripts) for the mouse and 13,910 for the human sequences. Of these, >4,300 were unique to Consortium libraries. We have assembled a core clone set containing one cDNA for each assembly group for the mouse and have constructed the corresponding microarray, termed "PancChip 4.0," which contains >9,000 nonredundant elements. We show that this PancChip is highly enriched for genes expressed in the endocrine pancreas. The mouse and human clone sets and corresponding arrays will be important resources for diabetes research.

Animals↗
PubMed2002

Design and implementation of microarray gene expression markup language (MAGE-ML).

BACKGROUND: Meaningful exchange of microarray data is currently difficult because it is rare that published data provide sufficient information depth or are even in the same format from one publication to another. Only when data can be easily exchanged will the entire biological community be able to derive the full benefit from such microarray studies. RESULTS: To this end we have developed three key ingredients towards standardizing the storage and exchange of microarray data. First, we have created a minimal information for the annotation of a microarray experiment (MIAME)-compliant conceptualization of microarray experiments modeled using the unified modeling language (UML) named MAGE-OM (microarray gene expression object model). Second, we have translated MAGE-OM into an XML-based data format, MAGE-ML, to facilitate the exchange of data. Third, some of us are now using MAGE (or its progenitors) in data production settings. Finally, we have developed a freely available software tool kit (MAGE-STK) that eases the integration of MAGE-ML into end users' systems. CONCLUSIONS: MAGE will help microarray data producers and users to exchange information by providing a common platform for data exchange, and MAGE-STK will make the adoption of MAGE easier.

Computer Simulation↗
PubMed2002

Functional genomics of the endocrine pancreas: the pancreas clone set and PancChip, new resources for diabetes research.

Over the past 5 years, microarrays have greatly facilitated large-scale analysis of gene expression levels. Although these arrays were not specifically geared to represent tissues and pathways known to be affected by diabetes, they have been used in both type 1 and type 2 diabetes research. To prepare a tool that is particularly useful in the study of type 1 diabetes, we have assembled a nonredundant set of 3,400 clones representing genes expressed in the mouse pancreas or pathways known to be affected by diabetes. We have demonstrated the usefulness of this clone set by preparing a cDNA glass microarray, the PancChip, and using it to analyze pancreatic gene expression from embryonic day 14.5 through adulthood in mice. The clone set and corresponding array are useful resources for diabetes research.

Adult↗