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1.
Bioinformatics ; 2020 Feb 25.
Artigo em Inglês | MEDLINE | ID: mdl-32096826

RESUMO

MOTIVATION: Reverse vaccinology (RV) is a milestone in rational vaccine design, and machine learning (ML) has been applied to enhance the accuracy of RV prediction. However, ML-based RV still faces the challenges in prediction accuracy and program accessibility. RESULTS: This study presents Vaxign-ML, a supervised ML classification to predict bacterial protective antigens. To identify the best ML method with optimized conditions, five ML methods were tested with biological and physiochemical features extracted from well-defined training data. Nested five-fold cross-validation and leave-one-pathogen-out validation were used to ensure unbiased performance assessment and the capability to predict vaccine candidates against a new emerging pathogen. The best performing model, Vaxign-ML, was compared to three publicly available RV programs with a high-quality benchmark dataset. Vaxign-ML showed superior performance in predicting bacterial protective antigens. Vaxign-ML is deployed in a publicly available web server. AVAILABILITY: Vaxign-ML website at http://www.violinet.org/vaxign/vaxign-ml. Docker standalone Vaxign-ML available at https://hub.docker.com/r/e4ong1031/vaxign-ml and source code is available at https://github.com/VIOLINet/Vaxign-ML-docker. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

2.
Infect Genet Evol ; 80: 104186, 2020 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-31923726

RESUMO

Tuberculosis (TB) is the leading infectious cause of death worldwide and claimed over 1.6 million lives in 2017. Furthermore, one-third of the world population is estimated to be latently infected with Mycobacterium tuberculosis (MTB). A safe and effective MTB vaccine that can prevent both the primary infection and the reactivation of latent tuberculosis infection (LTBI), and that can protect against all forms of TB in adults and adolescents is urgently needed. In this study, using computational approaches, we predicted the capacity of the epitopes to be presented by the HLA molecules for ten MTB protein antigens (Mtb39a, Mtb32a, Ag85B, ESAT-6, TB10.4, Rv2660, Rv2608, Rv3619, Rv3620, and Rv1813) constituting five MTB subunit vaccines (M72, H1, H4, H56, and ID93) that are currently in clinical trials. We also assessed the promiscuity of the predicted epitopes based on a reference set of alleles and supertype alleles, and estimated the population coverage of the ten antigens in three high TB burden countries (China, India, and South Africa). Among the ten antigens evaluated, Rv2608 was found to have the highest number of promiscuous epitopes predicted to bind the most MHC-I and MHC-II supertype alleles, highest predicted immunogenicity, and the broadest population coverage in three high burden countries. Between the two latency-related antigens (Rv1813 and Rv2660), Rv1813 was predicted to have a better epitope diversity and promiscuity, immunogenicity, and population coverage. As a result, the ID93 vaccine consisted of Rv2608, Rv1813, Rv3619, and Rv3620 was predicted to have the best potential for preventing both active and latent TB infection. Our results highlighted the importance and usefulness of a systematic and comprehensive assessment of protein antigens using computational approaches in MTB vaccine development.

3.
Methods Mol Biol ; 2074: 165-179, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-31583638

RESUMO

Modern large-scale biological data analysis often generates a set of significant genes, frequently associated with scores. Pathway-based approaches are routinely performed to understand the functional contexts of these genes. Reactome is the most comprehensive open-access biological pathway knowledge base, widely used in the research community, providing a solid foundation for pathway-based data analysis. ReactomeFIViz is a Cytoscape app built upon Reactome pathways to help users perform pathway- and network-based data analysis and visualization. In this chapter we describe procedures on how to perform pathway enrichment analysis using ReactomeFIViz for a gene score file. We describe two types of analysis: pathway enrichment based on a set of significant genes and GSEA analysis using gene scores without cutoff. We also describe a feature to overlay gene scores onto pathway diagrams, enabling users to understand the underlying mechanisms for up- or down- regulated pathways collected from pathway analysis.

4.
BMC Bioinformatics ; 20(Suppl 21): 704, 2019 Dec 23.
Artigo em Inglês | MEDLINE | ID: mdl-31865910

RESUMO

BACKGROUND: Different human responses to the same vaccine were frequently observed. For example, independent studies identified overlapping but different transcriptomic gene expression profiles in Yellow Fever vaccine 17D (YF-17D) immunized human subjects. Different experimental and analysis conditions were likely contributed to the observed differences. To investigate this issue, we developed a Vaccine Investigation Ontology (VIO), and applied VIO to classify the different variables and relations among these variables systematically. We then evaluated whether the ontological VIO modeling and VIO-based statistical analysis would contribute to the enhanced vaccine investigation studies and a better understanding of vaccine response mechanisms. RESULTS: Our VIO modeling identified many variables related to data processing and analysis such as normalization method, cut-off criteria, software settings including software version. The datasets from two previous studies on human responses to YF-17D vaccine, reported by Gaucher et al. (2008) and Querec et al. (2009), were re-analyzed. We first applied the same LIMMA statistical method to re-analyze the Gaucher data set and identified a big difference in terms of significantly differentiated gene lists compared to the original study. The different results were likely due to the LIMMA version and software package differences. Our second study re-analyzed both Gaucher and Querec data sets but with the same data processing and analysis pipeline. Significant differences in differential gene lists were also identified. In both studies, we found that Gene Ontology (GO) enrichment results had more overlapping than the gene lists and enriched pathway lists. The visualization of the identified GO hierarchical structures among the enriched GO terms and their associated ancestor terms using GOfox allowed us to find more associations among enriched but often different GO terms, demonstrating the usage of GO hierarchical relations enhance data analysis. CONCLUSIONS: The ontology-based analysis framework supports standardized representation, integration, and analysis of heterogeneous data of host responses to vaccines. Our study also showed that differences in specific variables might explain different results drawn from similar studies.


Assuntos
Vacinas , Ontologias Biológicas , Humanos , Software
5.
BMC Bioinformatics ; 20(Suppl 5): 180, 2019 Apr 25.
Artigo em Inglês | MEDLINE | ID: mdl-31272389

RESUMO

BACKGROUND: Stem cells and stem cell lines are widely used in biomedical research. The Cell Ontology (CL) and Cell Line Ontology (CLO) are two community-based OBO Foundry ontologies in the domains of in vivo cells and in vitro cell line cells, respectively. RESULTS: To support standardized stem cell investigations, we have developed an Ontology for Stem Cell Investigations (OSCI). OSCI imports stem cell and cell line terms from CL and CLO, and investigation-related terms from existing ontologies. A novel focus of OSCI is its application in representing metadata types associated with various stem cell investigations. We also applied OSCI to systematically categorize experimental variables in an induced pluripotent stem cell line cell study related to bipolar disorder. In addition, we used a semi-automated literature mining approach to identify over 200 stem cell gene markers. The relations between these genes and stem cells are modeled and represented in OSCI. CONCLUSIONS: OSCI standardizes stem cells found in vivo and in vitro and in various stem cell investigation processes and entities. The presented use cases demonstrate the utility of OSCI in iPSC studies and literature mining related to bipolar disorder.


Assuntos
Ontologias Biológicas , Pesquisa Biomédica/normas , Animais , Humanos , Células-Tronco
6.
BMC Bioinformatics ; 20(Suppl 7): 199, 2019 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-31074377

RESUMO

BACKGROUND: Drug adverse events (AEs), or called adverse drug events (ADEs), are ranked one of the leading causes of mortality. The Ontology of Adverse Events (OAE) has been widely used for adverse event AE representation, standardization, and analysis. OAE-based ADE-specific ontologies, including ODNAE for drug-associated neuropathy-inducing AEs and OCVDAE for cardiovascular drug AEs, have also been developed and used. However, these ADE-specific ontologies do not consider the effects of other factors (e.g., age and drug-treated disease) on the outcomes of ADEs. With more ontological studies of ADEs, it is also critical to develop a general purpose ontology for representing ADEs for various types of drugs. RESULTS: Our survey of FDA drug package insert documents and other resources for 224 neuropathy-inducing drugs discovered that many drugs (e.g., sirolimus and linezolid) cause different AEs given patients' age or the diseases treated by the drugs. To logically represent the complex relations among drug, drug ingredient and mechanism of action, AE, age, disease, and other related factors, an ontology design pattern was developed and applied to generate a community-driven open-source Ontology of Drug Adverse Events (ODAE). The ODAE development follows the OBO Foundry ontology development principles (e.g., openness and collaboration). Built on a generalizable ODAE design pattern and extending the OAE and NDF-RT ontology, ODAE has represented various AEs associated with the over 200 neuropathy-inducing drugs given different age and disease conditions. ODAE is now deposited in the Ontobee for browsing and queries. As a demonstration of usage, a SPARQL query of the ODAE knowledge base was developed to identify all the drugs having the mechanisms of ion channel interactions, the diseases treated with the drugs, and AEs after the treatment in adult patients. AE-specific drug class effects were also explored using ODAE and SPARQL. CONCLUSION: ODAE provides a general representation of ADEs given different conditions and can be used for querying scientific questions. ODAE is also a robust knowledge base and platform for semantic and logic representation and study of ADEs of more drugs in the future.


Assuntos
Sistemas de Notificação de Reações Adversas a Medicamentos/estatística & dados numéricos , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/etiologia , Linezolida/efeitos adversos , Doenças do Sistema Nervoso/induzido quimicamente , Preparações Farmacêuticas/administração & dosagem , Sirolimo/efeitos adversos , Software , Adulto , Fatores Etários , Antibacterianos/efeitos adversos , Antibióticos Antineoplásicos/efeitos adversos , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/patologia , Humanos , Preparações Farmacêuticas/análise
7.
Nucleic Acids Res ; 47(D1): D693-D700, 2019 Jan 08.
Artigo em Inglês | MEDLINE | ID: mdl-30365026

RESUMO

Virulence factors (VFs) are molecules that allow microbial pathogens to overcome host defense mechanisms and cause disease in a host. It is critical to study VFs for better understanding microbial pathogenesis and host defense mechanisms. Victors (http://www.phidias.us/victors) is a novel, manually curated, web-based integrative knowledge base and analysis resource for VFs of pathogens that cause infectious diseases in human and animals. Currently, Victors contains 5296 VFs obtained via manual annotation from peer-reviewed publications, with 4648, 179, 105 and 364 VFs originating from 51 bacterial, 54 viral, 13 parasitic and 8 fungal species, respectively. Our data analysis identified many VF-specific patterns. Within the global VF pool, cytoplasmic proteins were more common, while adhesins were less common compared to findings on protective vaccine antigens. Many VFs showed homology with host proteins and the human proteins interacting with VFs represented the hubs of human-pathogen interactions. All Victors data are queriable with a user-friendly web interface. The VFs can also be searched by a customized BLAST sequence similarity searching program. These VFs and their interactions with the host are represented in a machine-readable Ontology of Host-Pathogen Interactions. Victors supports the 'One Health' research as a vital source of VFs in human and animal pathogens.

8.
J Biomed Semantics ; 9(1): 3, 2018 01 12.
Artigo em Inglês | MEDLINE | ID: mdl-29329592

RESUMO

Ontologies are critical to data/metadata and knowledge standardization, sharing, and analysis. With hundreds of biological and biomedical ontologies developed, it has become critical to ensure ontology interoperability and the usage of interoperable ontologies for standardized data representation and integration. The suite of web-based Ontoanimal tools (e.g., Ontofox, Ontorat, and Ontobee) support different aspects of extensible ontology development. By summarizing the common features of Ontoanimal and other similar tools, we identified and proposed an "eXtensible Ontology Development" (XOD) strategy and its associated four principles. These XOD principles reuse existing terms and semantic relations from reliable ontologies, develop and apply well-established ontology design patterns (ODPs), and involve community efforts to support new ontology development, promoting standardized and interoperable data and knowledge representation and integration. The adoption of the XOD strategy, together with robust XOD tool development, will greatly support ontology interoperability and robust ontology applications to support data to be Findable, Accessible, Interoperable and Reusable (i.e., FAIR).


Assuntos
Ontologias Biológicas , Semântica , Software
9.
Front Immunol ; 8: 1382, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-29123525

RESUMO

With many protective vaccine antigens reported in the literature and verified experimentally, how to use the knowledge mined from these antigens to support rational vaccine design and study underlying design mechanism remains unclear. In order to address the problem, a systematic bioinformatics analysis was performed on 291 Gram-positive and Gram-negative bacterial protective antigens with experimental evidence manually curated in the Protegen database. The bioinformatics analyses evaluated included subcellular localization, adhesin probability, peptide signaling, transmembrane α-helix and ß-barrel, conserved domain, Clusters of Orthologous Groups, and Gene Ontology functional annotations. Here we showed the critical role of adhesins, along with subcellular localization, peptide signaling, in predicting secreted extracellular or surface-exposed protective antigens, with mechanistic explanations supported by functional analysis. We also found a significant negative correlation of transmembrane α-helix to antigen protectiveness in Gram-positive and Gram-negative pathogens, while a positive correlation of transmembrane ß-barrel was observed in Gram-negative pathogens. The commonly less-focused cytoplasmic and cytoplasmic membrane proteins could be potentially predicted with the help of other selection criteria such as adhesin probability and functional analysis. The significant findings in this study can support rational vaccine design and enhance our understanding of vaccine design mechanisms.

10.
Infect Genet Evol ; 55: 244-250, 2017 11.
Artigo em Inglês | MEDLINE | ID: mdl-28941991

RESUMO

H56/AERAS-456+IC31 (H56), composed of two early secretion proteins, Ag85B and ESAT-6, and a latency associated protein, Rv2660, and the IC31 Intercell adjuvant, is a new fusion subunit vaccine candidate designed to induce immunity against both new infection and reactivation of latent tuberculosis infection. Efficacy of subunit vaccines may be affected by the diversity of vaccine antigens among clinical strains and the extent of recognition by the diverse HLA molecules in the recipient population. Although a previous study showed the conservative nature of Ag85B- and ESAT-6-encoding genes, genetic diversity of Rv2660c that encodes RV2660 is largely unknown. The population coverage of H56 as a whole yet remains to be assessed. The present study was conducted to address these important knowledge gaps. DNA sequence analysis of Rv2660c found no variation among 83 of the 84 investigated clinical strains belonging to four genetic lineages. H56 was predicted to have as high as 99.6% population coverage in the South Africa population using the Immune Epitope Database (IEDB) Population Coverage Tool. Further comparison of H56 population coverage between South African Blacks and Caucasians based on the phenotypic frequencies of binding MHC Class I and Class II supertype alleles found that all of the nine MHC-I and six of eight MHC-II human leukocyte antigen (HLA) supertype alleles analyzed were significantly differentially expressed between the two subpopulations. This finding suggests the presence of race-specific functional binding motifs of MHC-I and MHC-II HLA alleles, which, in turn, highlights the importance of including diverse populations in vaccine clinical evaluation. In conclusion, H56 vaccine is predicted to have a promising population coverage in South Africa; this study demonstrates the utility of integrating comparative genomics and bioinformatics in bridging animal and clinical studies of novel TB vaccines.


Assuntos
Antígenos de Bactérias/genética , Antígenos de Bactérias/imunologia , Evolução Molecular , Mycobacterium tuberculosis/genética , Mycobacterium tuberculosis/imunologia , Vacinas contra a Tuberculose/imunologia , Tuberculose/imunologia , Tuberculose/prevenção & controle , Mapeamento de Epitopos , Variação Genética , Antígenos HLA/genética , Antígenos HLA/imunologia , Humanos , Seleção Genética , África do Sul/epidemiologia , Vacinas contra a Tuberculose/genética , Vacinas de Subunidades/imunologia
11.
Int J Mol Sci ; 18(2)2017 Feb 21.
Artigo em Inglês | MEDLINE | ID: mdl-28230771

RESUMO

As one of the most influential and troublesome human pathogens, Acinetobacter baumannii (A. baumannii) has emerged with many multidrug-resistant strains. After collecting 33 complete A. baumannii genomes and 84 representative antibiotic resistance determinants, we used the Vaxign reverse vaccinology approach to predict classical type vaccine candidates against A. baumannii infections and new type vaccine candidates against antibiotic resistance. Our genome analysis identified 35 outer membrane or extracellular adhesins that are conserved among all 33 genomes, have no human protein homology, and have less than 2 transmembrane helices. These 35 antigens include 11 TonB dependent receptors, 8 porins, 7 efflux pump proteins, and 2 fimbrial proteins (FilF and CAM87009.1). CAM86003.1 was predicted to be an adhesin outer membrane protein absent from 3 antibiotic-sensitive strains and conserved in 21 antibiotic-resistant strains. Feasible anti-resistance vaccine candidates also include one extracellular protein (QnrA), 3 RND type outer membrane efflux pump proteins, and 3 CTX-M type ß-lactamases. Among 39 ß-lactamases, A. baumannii CTX-M-2, -5, and -43 enzymes are predicted as adhesins and better vaccine candidates than other ß-lactamases to induce preventive immunity and enhance antibiotic treatments. This report represents the first reverse vaccinology study to systematically predict vaccine antigen candidates against antibiotic resistance for a microbial pathogen.


Assuntos
Acinetobacter baumannii/efeitos dos fármacos , Acinetobacter baumannii/imunologia , Vacinas Bacterianas/imunologia , Farmacorresistência Bacteriana/imunologia , Epitopos/imunologia , Infecções por Acinetobacter/imunologia , Infecções por Acinetobacter/prevenção & controle , Acinetobacter baumannii/genética , Sequência de Aminoácidos , Antibacterianos/farmacologia , Biologia Computacional/métodos , Sequência Conservada , Epitopos/química , Epitopos/genética , Genes Bacterianos , Genoma Bacteriano , Genômica/métodos , Humanos , Testes de Sensibilidade Microbiana
12.
Nucleic Acids Res ; 45(D1): D347-D352, 2017 01 04.
Artigo em Inglês | MEDLINE | ID: mdl-27733503

RESUMO

Linked Data (LD) aims to achieve interconnected data by representing entities using Unified Resource Identifiers (URIs), and sharing information using Resource Description Frameworks (RDFs) and HTTP. Ontologies, which logically represent entities and relations in specific domains, are the basis of LD. Ontobee (http://www.ontobee.org/) is a linked ontology data server that stores ontology information using RDF triple store technology and supports query, visualization and linkage of ontology terms. Ontobee is also the default linked data server for publishing and browsing biomedical ontologies in the Open Biological Ontology (OBO) Foundry (http://obofoundry.org) library. Ontobee currently hosts more than 180 ontologies (including 131 OBO Foundry Library ontologies) with over four million terms. Ontobee provides a user-friendly web interface for querying and visualizing the details and hierarchy of a specific ontology term. Using the eXtensible Stylesheet Language Transformation (XSLT) technology, Ontobee is able to dereference a single ontology term URI, and then output RDF/eXtensible Markup Language (XML) for computer processing or display the HTML information on a web browser for human users. Statistics and detailed information are generated and displayed for each ontology listed in Ontobee. In addition, a SPARQL web interface is provided for custom advanced SPARQL queries of one or multiple ontologies.


Assuntos
Ontologias Biológicas , Bases de Dados Factuais , Software , Navegador
13.
BMC Bioinformatics ; 18(Suppl 17): 557, 2017 12 21.
Artigo em Inglês | MEDLINE | ID: mdl-29322915

RESUMO

BACKGROUND: The Experimental Factor Ontology (EFO) is an application ontology driven by experimental variables including cell lines to organize and describe the diverse experimental variables and data resided in the EMBL-EBI resources. The Cell Line Ontology (CLO) is an OBO community-based ontology that contains information of immortalized cell lines and relevant experimental components. EFO integrates and extends ontologies from the bio-ontology community to drive a number of practical applications. It is desirable that the community shares design patterns and therefore that EFO reuses the cell line representation from the Cell Line Ontology (CLO). There are, however, challenges to be addressed when developing a common ontology design pattern for representing cell lines in both EFO and CLO. RESULTS: In this study, we developed a strategy to compare and map cell line terms between EFO and CLO. We examined Cellosaurus resources for EFO-CLO cross-references. Text labels of cell lines from both ontologies were verified by biological information axiomatized in each source. The study resulted in the identification 873 EFO-CLO aligned and 344 EFO unique immortalized permanent cell lines. All of these cell lines were updated to CLO and the cell line related information was merged. A design pattern that integrates EFO and CLO was also developed. CONCLUSION: Our study compared, aligned, and synchronized the cell line information between CLO and EFO. The final updated CLO will be examined as the candidate ontology to import and replace eligible EFO cell line classes thereby supporting the interoperability in the bio-ontology domain. Our mapping pipeline illustrates the use of ontology in aiding biological data standardization and integration through the biological and semantics content of cell lines.


Assuntos
Algoritmos , Ontologias Biológicas , Fenômenos Fisiológicos Celulares , Biologia Computacional/métodos , Bases de Dados Factuais , Perfilação da Expressão Gênica , Linhagem Celular , Mineração de Dados , Humanos , Semântica
14.
BMC Bioinformatics ; 18(Suppl 17): 556, 2017 12 21.
Artigo em Inglês | MEDLINE | ID: mdl-29322930

RESUMO

BACKGROUND: Aiming to understand cellular responses to different perturbations, the NIH Common Fund Library of Integrated Network-based Cellular Signatures (LINCS) program involves many institutes and laboratories working on over a thousand cell lines. The community-based Cell Line Ontology (CLO) is selected as the default ontology for LINCS cell line representation and integration. RESULTS: CLO has consistently represented all 1097 LINCS cell lines and included information extracted from the LINCS Data Portal and ChEMBL. Using MCF 10A cell line cells as an example, we demonstrated how to ontologically model LINCS cellular signatures such as their non-tumorigenic epithelial cell type, three-dimensional growth, latrunculin-A-induced actin depolymerization and apoptosis, and cell line transfection. A CLO subset view of LINCS cell lines, named LINCS-CLOview, was generated to support systematic LINCS cell line analysis and queries. In summary, LINCS cell lines are currently associated with 43 cell types, 131 tissues and organs, and 121 cancer types. The LINCS-CLO view information can be queried using SPARQL scripts. CONCLUSIONS: CLO was used to support ontological representation, integration, and analysis of over a thousand LINCS cell line cells and their cellular responses.


Assuntos
Mama/metabolismo , Biologia Computacional/métodos , Regulação da Expressão Gênica , Ensaios de Triagem em Larga Escala , Neoplasias/genética , Apoptose/efeitos dos fármacos , Mama/citologia , Mama/efeitos dos fármacos , Linhagem Celular , Células Cultivadas , Feminino , Perfilação da Expressão Gênica , Humanos , Macrolídeos/farmacologia , Neoplasias/tratamento farmacológico , Neoplasias/patologia , Tiazolidinas/farmacologia
15.
AMIA Annu Symp Proc ; 2017: 1793-1801, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-29854250

RESUMO

A critical issue in the usage of cancer drugs is its association with various adverse events (AEs) in some, but not all, patients. The National Cancer Institute (NCI) Common Terminology Criteria for Adverse Events (CTCAE) is a controlled terminology for AE classification and analysis in cancer clinical trials. The Ontology of Adverse Events (OAE) is a community-based ontology in the domain of AEs. In this study, OAE was first updated by including AE severity grading and OAE-CTCAE mapping. An OAE subset containing CTCAE-related terms and their associated OAE terms was generated to facilitate term usage. A use case study based on a published cancer drug clinical trial demonstrates that OAE provides better hierarchical representation, includes semantic relations, and supports automated reasoning. Demonstrated with a single patient analysis, the OAE framework supports precision informatics for representing AEs and related genetic and clinical conditions in individual patients treated with cancer drugs.


Assuntos
Antineoplásicos/efeitos adversos , Ontologias Biológicas , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/classificação , Neoplasias/tratamento farmacológico , Farmacovigilância , Antineoplásicos/uso terapêutico , Humanos , Informática Médica , Semântica , Índice de Gravidade de Doença
17.
Artigo em Inglês | MEDLINE | ID: mdl-27570653

RESUMO

Hundreds of biological and biomedical ontologies have been developed to support data standardization, integration and analysis. Although ontologies are typically developed for community usage, community efforts in ontology development are limited. To support ontology visualization, distribution, and community-based annotation and development, we have developed Ontokiwi, an ontology extension to the MediaWiki software. Ontokiwi displays hierarchical classes and ontological axioms. Ontology classes and axioms can be edited and added using Ontokiwi form or MediaWiki source editor. Ontokiwi also inherits MediaWiki features such as Wikitext editing and version control. Based on the Ontokiwi/MediaWiki software package, we have developed Ontobedia, which targets to support community-based development and annotations of biological and biomedical ontologies. As demonstrations, we have loaded the Ontology of Adverse Events (OAE) and the Cell Line Ontology (CLO) into Ontobedia. Our studies showed that Ontobedia was able to achieve expected Ontokiwi features.

18.
PLoS One ; 10(6): e0126718, 2015.
Artigo em Inglês | MEDLINE | ID: mdl-26042811

RESUMO

Cell-based therapies to treat skeletal muscle disease are limited by the poor survival of donor myoblasts, due in part to acute hypoxic stress. After confirming that the microenvironment of transplanted myoblasts is hypoxic, we screened a kinase inhibitor library in vitro and identified five kinase inhibitors that protected myoblasts from cell death or growth arrest in hypoxic conditions. A systematic, combinatorial study of these compounds further improved myoblast viability, showing both synergistic and additive effects. Pathway and target analysis revealed CDK5, CDK2, CDC2, WEE1, and GSK3ß as the main target kinases. In particular, CDK5 was the center of the target kinase network. Using our recently developed statistical method based on elastic net regression we computationally validated the key role of CDK5 in cell protection against hypoxia. This method provided a list of potential kinase targets with a quantitative measure of their optimal amount of relative inhibition. A modified version of the method was also able to predict the effect of combinations using single-drug response data. This work is the first step towards a broadly applicable system-level strategy for the pharmacology of hypoxic damage.


Assuntos
Pontos de Checagem do Ciclo Celular/efeitos dos fármacos , Mioblastos Esqueléticos/enzimologia , Inibidores de Proteínas Quinases/farmacologia , Proteínas Quinases/metabolismo , Animais , Morte Celular/efeitos dos fármacos , Hipóxia Celular/efeitos dos fármacos , Células Cultivadas , Camundongos , Camundongos Endogâmicos NOD , Camundongos SCID , Camundongos Transgênicos , Mioblastos Esqueléticos/patologia
19.
J Comput Biol ; 22(4): 266-88, 2015 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-25844667

RESUMO

A key aim of systems biology is the reconstruction of molecular networks. We do not yet, however, have networks that integrate information from all datasets available for a particular clinical condition. This is in part due to the limited scalability, in terms of required computational time and power, of existing algorithms. Network reconstruction methods should also be scalable in the sense of allowing scientists from different backgrounds to efficiently integrate additional data. We present a network model of acute myeloid leukemia (AML). In the current version (AML 2.1), we have used gene expression data (both microarray and RNA-seq) from 5 different studies comprising a total of 771 AML samples and a protein-protein interactions dataset. Our scalable network reconstruction method is in part based on the well-known property of gene expression correlation among interacting molecules. The difficulty of distinguishing between direct and indirect interactions is addressed by optimizing the coefficient of variation of gene expression, using a validated gold-standard dataset of direct interactions. Computational time is much reduced compared to other network reconstruction methods. A key feature is the study of the reproducibility of interactions found in independent clinical datasets. An analysis of the most significant clusters, and of the network properties (intraset efficiency, degree, betweenness centrality, and PageRank) of common AML mutations demonstrated the biological significance of the network. A statistical analysis of the response of blast cells from 11 AML patients to a library of kinase inhibitors provided an experimental validation of the network. A combination of network and experimental data identified CDK1, CDK2, CDK4, and CDK6 and other kinases as potential therapeutic targets in AML.


Assuntos
Redes Reguladoras de Genes , Leucemia Mieloide Aguda/genética , Mapas de Interação de Proteínas , Antineoplásicos/farmacologia , Regulação Leucêmica da Expressão Gênica , Ontologia Genética , Humanos , Leucemia Mieloide Aguda/tratamento farmacológico , Leucemia Mieloide Aguda/metabolismo , Terapia de Alvo Molecular , Mutação , Inibidores de Proteínas Quinases/farmacologia , Reprodutibilidade dos Testes , Transcriptoma
20.
PLoS One ; 9(7): e102221, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25029499

RESUMO

The BCR-ABL translocation is found in chronic myeloid leukemia (CML) and in Ph+ acute lymphoblastic leukemia (ALL) patients. Although imatinib and its analogues have been used as front-line therapy to target this mutation and control the disease for over a decade, resistance to the therapy is still observed and most patients are not cured but need to continue the therapy indefinitely. It is therefore of great importance to find new therapies, possibly as drug combinations, which can overcome drug resistance. In this study, we identified eleven candidate anti-leukemic drugs that might be combined with imatinib, using three approaches: a kinase inhibitor library screen, a gene expression correlation analysis, and literature analysis. We then used an experimental search algorithm to efficiently explore the large space of possible drug and dose combinations and identified drug combinations that selectively kill a BCR-ABL+ leukemic cell line (K562) over a normal fibroblast cell line (IMR-90). Only six iterations of the algorithm were needed to identify very selective drug combinations. The efficacy of the top forty-nine combinations was further confirmed using Ph+ and Ph- ALL patient cells, including imatinib-resistant cells. Collectively, the drug combinations and methods we describe might be a first step towards more effective interventions for leukemia patients, especially those with the BCR-ABL translocation.


Assuntos
Protocolos de Quimioterapia Combinada Antineoplásica , Benzamidas/administração & dosagem , Benzamidas/farmacologia , Descoberta de Drogas , Proteínas de Fusão bcr-abl/metabolismo , Leucemia Mielogênica Crônica BCR-ABL Positiva/tratamento farmacológico , Piperazinas/administração & dosagem , Piperazinas/farmacologia , Pirimidinas/administração & dosagem , Pirimidinas/farmacologia , Algoritmos , Antineoplásicos/administração & dosagem , Antineoplásicos/farmacologia , Antineoplásicos/uso terapêutico , Benzamidas/uso terapêutico , Linhagem Celular Tumoral , Relação Dose-Resposta a Droga , Resistencia a Medicamentos Antineoplásicos , Humanos , Mesilato de Imatinib , Leucemia Mielogênica Crônica BCR-ABL Positiva/metabolismo , Leucemia Mielogênica Crônica BCR-ABL Positiva/patologia , Piperazinas/uso terapêutico , Pirimidinas/uso terapêutico
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