Assessment of protein set coherence using functional annotations

12 pages, 5 figures. -- PMID: 18937846 [PubMed].-- PMCID: PMC2588600.-- Additional information available: File 1: Coherence score and significance measures of random sets.- File 2: Functional analysis of 'Module 39' obtained by Pu et al. [37] using various approaches.[Background] Analysis of large-scale experimental datasets frequently produces one or more sets of proteins that are subsequently mined for functional interpretation and validation. To this end, a number of computational methods have been devised that rely on the analysis of functional annotations. Although current methods provide valuable information (e.g. significantly enriched annotations, pairwise functional similarities), they do not specifically measure the degree of homogeneity of a protein set.[Results] In this work we present a method that scores the degree of functional homogeneity, or coherence, of a set of proteins on the basis of the global similarity of their functional annotations. The method uses statistical hypothesis testing to assess the significance of the set in the context of the functional space of a reference set. As such, it can be used as a first step in the validation of sets expected to be homogeneous prior to further functional interpretation.[Conclusions] We evaluate our method by analysing known biologically relevant sets as well as random ones. The known relevant sets comprise macromolecular complexes, cellular components and pathways described for Saccharomyces cerevisiae, which are mostly significantly coherent. Finally, we illustrate the usefulness of our approach for validating ‘functional modules’ obtained from computational analysis of protein-protein interaction networks.Matlab code and supplementary data are available at: http://www.cnb.csic.es/~monica/coherence/This work has been partially funded by the Spanish grants BIO2007-67150-C03-02, S-Gen- 0166/2006, CYTED-505PI0058, TIN2005-5619, PR27/05-13964-BSCH. APM acknowledges the support of the Spanish Ramón y Cajal program.Peer reviewe

MACS: Multi-agent COTR system for Defense Contracting

The field of intelligent multi-agent systems has expanded rapidly in the recent past. Multi-agent architectures and systems are being investigated and continue to develop. To date, little has been accomplished in applying multi-agent systems to the defense acquisition domain. This paper describes the design, development, and related considerations of a multi-agent system in the area of procurement and contracting for the defense acquisition community

Determination of Hexamethylene Bisacetamide, An Antineoplastic Compound, in Mouse and Human Plasma by LC–MS/MS

Hexamethylene bisacetamide (HMBA) is a polar compound which has recently been discovered to have antineoplastic activity by up-regulating the expression of an endogenous antiproliferative breast cancer protein, HEXIM1 (hexamethylene bisacetamide inducible protein 1) in vivo. HMBA has been shown in the past to induce terminal differentiation in multiple leukemia types at a concentration of 2–5 mM, but its phase I and II clinical trials were largely unsuccessful due to serious side effects (notably, thrombocytopenia) with dose escalation. In this work, a sensitive and simple LC–MS/MS method for direct determination of HMBA in mouse and human plasma is described. Plasma samples were prepared by deproteinization with acetonitrile. Separation was achieved on a Waters Atlantis® T3 (2.1 mm × 50 mm, 3 μm) column with retention times of 2.2 and 3.7 min for HMBA and 7MBA (internal standard), respectively. The quantitation was carried out by tandem mass spectrometry using positive MRM mode. The linear range of the method was 0.500–100 ng/mL in both mouse and human plasma with injection volume of 5 μL. This method has been validated in accordance with the US Food and Drug Administration (FDA) guidelines for bioanalytical method development and applied to the determination of HMBA concentrations in FVB mice over time after a single dose of HMBA in saline (0.9% NaCl) at 10 mg/kg

Lead Optimization of HMBA to Develop Potent HEXIM1 Inducers

The potency of a series of Hexamethylene bis-acetamide (HMBA) derivatives inducing Hexamethylene bis-acetamide inducible protein 1 (HEXIM1) was determined in LNCaP prostate cancer cells. Several compounds with unsymmetrical structures showed significantly improved activity. Distinct from HMBA, these analogs have increased hydrophobicity and can improve the short half-life of HMBA, which is one of the factors that have limited the application of HMBA in clinics. The unsymmetrical scaffolds of the new analogs provide the basis for further lead optimization of the compounds using combinatorial chemistry strategy

Discovering semantic features in the literature: a foundation for building functional associations

BACKGROUND: Experimental techniques such as DNA microarray, serial analysis of gene expression (SAGE) and mass spectrometry proteomics, among others, are generating large amounts of data related to genes and proteins at different levels. As in any other experimental approach, it is necessary to analyze these data in the context of previously known information about the biological entities under study. The literature is a particularly valuable source of information for experiment validation and interpretation. Therefore, the development of automated text mining tools to assist in such interpretation is one of the main challenges in current bioinformatics research. RESULTS: We present a method to create literature profiles for large sets of genes or proteins based on common semantic features extracted from a corpus of relevant documents. These profiles can be used to establish pair-wise similarities among genes, utilized in gene/protein classification or can be even combined with experimental measurements. Semantic features can be used by researchers to facilitate the understanding of the commonalities indicated by experimental results. Our approach is based on non-negative matrix factorization (NMF), a machine-learning algorithm for data analysis, capable of identifying local patterns that characterize a subset of the data. The literature is thus used to establish putative relationships among subsets of genes or proteins and to provide coherent justification for this clustering into subsets. We demonstrate the utility of the method by applying it to two independent and vastly different sets of genes. CONCLUSION: The presented method can create literature profiles from documents relevant to sets of genes. The representation of genes as additive linear combinations of semantic features allows for the exploration of functional associations as well as for clustering, suggesting a valuable methodology for the validation and interpretation of high-throughput experimental data

GENECODIS: a web-based tool for finding significant concurrent annotations in gene lists

We present GENECODIS, a web-based tool that integrates different sources of information to search for annotations that frequently co-occur in a set of genes and rank them by statistical significance. The analysis of concurrent annotations provides significant information for the biologic interpretation of high-throughput experiments and may outperform the results of standard methods for the functional analysis of gene lists. GENECODIS is publicly available at

Integrated analysis of gene expression by association rules discovery

BACKGROUND: Microarray technology is generating huge amounts of data about the expression level of thousands of genes, or even whole genomes, across different experimental conditions. To extract biological knowledge, and to fully understand such datasets, it is essential to include external biological information about genes and gene products to the analysis of expression data. However, most of the current approaches to analyze microarray datasets are mainly focused on the analysis of experimental data, and external biological information is incorporated as a posterior process. RESULTS: In this study we present a method for the integrative analysis of microarray data based on the Association Rules Discovery data mining technique. The approach integrates gene annotations and expression data to discover intrinsic associations among both data sources based on co-occurrence patterns. We applied the proposed methodology to the analysis of gene expression datasets in which genes were annotated with metabolic pathways, transcriptional regulators and Gene Ontology categories. Automatically extracted associations revealed significant relationships among these gene attributes and expression patterns, where many of them are clearly supported by recently reported work. CONCLUSION: The integration of external biological information and gene expression data can provide insights about the biological processes associated to gene expression programs. In this paper we show that the proposed methodology is able to integrate multiple gene annotations and expression data in the same analytic framework and extract meaningful associations among heterogeneous sources of data. An implementation of the method is included in the Engene software package

Transcriptional regulation by the estrogen receptor of antioxidative stress enzymes and its functional implications

We previously reported that antiestrogen-liganded estrogen receptor b (ERb) transcriptionally activates the major detoxifying enzyme quinone reductase (QR) (NAD(P)H:-quinone oxidoreductase). Our studies also indicate that upregulation of QR, either by overexpression or induction by tamoxifen, can protect breast cells against oxidative DNA damage caused by estrogen metabolites. We now report on the upregulation of glutathione S-transferases Pi (GST-Pi) and gamma-glutamylcysteine synthetase heavy subunit (GCSh) expression by antiestrogens. Studies indicate the regulation of GST-Pi and GCSh transcriptional activity by ER. While ER regulation is mediated by an electrophile response element (EpRE), we identified mechanistic differences in the involvement of other transcription factors. Regardless of these differences, ERb-mediated regulation of GST-Pi and GCSh point towards an important role for ERb in cellular protection against oxidative stress. A protective role is supported by our observation of inhibition of estrogeninduced DNA damage upon upregulation of GST-Pi and GCSh expression

bioNMF: a versatile tool for non-negative matrix factorization in biology

BACKGROUND: In the Bioinformatics field, a great deal of interest has been given to Non-negative matrix factorization technique (NMF), due to its capability of providing new insights and relevant information about the complex latent relationships in experimental data sets. This method, and some of its variants, has been successfully applied to gene expression, sequence analysis, functional characterization of genes and text mining. Even if the interest on this technique by the bioinformatics community has been increased during the last few years, there are not many available simple standalone tools to specifically perform these types of data analysis in an integrated environment. RESULTS: In this work we propose a versatile and user-friendly tool that implements the NMF methodology in different analysis contexts to support some of the most important reported applications of this new methodology. This includes clustering and biclustering gene expression data, protein sequence analysis, text mining of biomedical literature and sample classification using gene expression. The tool, which is named bioNMF, also contains a user-friendly graphical interface to explore results in an interactive manner and facilitate in this way the exploratory data analysis process. CONCLUSION: bioNMF is a standalone versatile application which does not require any special installation or libraries. It can be used for most of the multiple applications proposed in the bioinformatics field or to support new research using this method. This tool is publicly available at

Chronic Treatment with Ivabradine Does Not Affect Cardiovascular Autonomic Control in Rats

A low resting heart rate (HR) would be of great benefit in cardiovascular diseases. Ivabradine a novel selective inhibitor of hyperpolarization-activated cyclic nucleotide gated (HCN) channels- has emerged as a promising HR lowering drug. Its effects on the autonomic HR control are little known. This study assessed the effects of chronic treatment with ivabradine on the modulatory, reflex and tonic cardiovascular autonomic control and on the renal sympathetic nerve activity (RSNA). Male Wistar rats were divided in 2 groups, receiving intraperitoneal injections of vehicle (VEH) or ivabradine (IVA) during 7 or 8 consecutive days. Rats were submitted to vessels cannulation to perform arterial blood pressure (AP) and HR recordings in freely moving rats. Time series of resting pulse interval and systolic AP were used to measure cardiovascular variability parameters. We also assessed the baroreflex, chemoreflex and the Bezold-Jarish reflex sensitivities. To better evaluate the effects of ivabradine on the autonomic control of the heart, we performed sympathetic and vagal autonomic blockade. As expected, ivabradine treated rats showed a lower resting (VEH: 362 +/- 16 bpm vs. IVA: 260 +/- 14 bpm, p = 0.0005) and intrinsic HR (VEH: 369 +/- 9 bpm vs. IVA: 326 +/- 11 bpm, p = 0.0146). However, the chronic treatment with ivabradine did not change normalized HR spectral parameters LF (nu) (VEH: 24.2 +/- 4.6 vs. IVA: 29.8 +/- 6.4p > 0.05)HF (nu) (VEH: 75.1 +/- 3.7 vs. IVA: 69.2 +/- 5.8p > 0.05), any cardiovascular reflexes, neither the tonic autonomic control of the HR (tonic sympathovagal indexVEH: 0.91 +/- 0.02 vs. IVA: 0.88 +/- 0.03, p = 0.3494). We performed the AP, HR and RSNA recordings in urethane-anesthetized rats. The chronic treatment with ivabradine reduced the resting HR (VEH: 364 +/- 12 bpm vs. IVA: 207 +/- 11 bpm, p < 0.0001), without affecting RSNA (VEH: 117 +/- 16 vs. IVA: 120 +/- 9 spikes/s, p = 0.9100) and mean arterial pressure (VEH: 70 +/- 4 vs. IVA: 77 +/- 6 mmHg, p = 0.3293). Our results suggest that, in health rats, the long-term treatment with ivabradine directly reduces the HR without changing the RSNA modulation and the reflex and tonic autonomic control of the heart.Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)Fundacao de Amparo a Pesquisa de Minas Gerais (FAPEMIG)Universidade Federal de Ouro Preto (UFOP)Universidade Federal do Triangulo Mineiro (UFTM), BrazilUniv Fed Ouro Preto, Inst Exact & Biol Sci, Dept Biol Sci, Lab Cardiovasc Physiol, Ouro Preto, BrazilUniv Fed Ouro Preto, CBIOL NUPEB, Grad Program Biol Sci, Ouro Preto, BrazilUniv Fed Minas Gerais, Inst Biol Sci, Dept Physiol & Biophys, Lab Hypertens, Belo Horizonte, MG, BrazilUniv Fed Sao Paulo, Inst Sci & Technol, Biomed Engn Lab, Sao Jose Dos Campos, BrazilUniv Uberaba, Dept Physiol, Uberaba, BrazilUniv Milan, Osped Maggiore Policlin, IRCCS Ca Granda Fdn, Dept Clin Sci & Community Hlth, Milan, ItalyFed Univ Trianaulo Pvlineiro, Inst Biol & Nat Sci, Dept Physiol, Uberaba, BrazilUniv Fed Sao Paulo, Inst Sci & Technol, Biomed Engn Lab, Sao Jose Dos Campos, BrazilCNPq: 400851/2014-8Web of Scienc