Data Mining Approaches to Diffuse Large B–Cell Lymphoma Gene Expression Data Interpretation

This paper presents a comprehensive study of gene expression patterns originating from a diffuse large B–cell lymphoma (DLBCL) database. It focuses on the implementation of feature selection and classification techniques. Thus, it firstly tackles the identification of relevant genes for the prediction of DLBCL types. It also allows the determination of key biomarkers to differentiate two subtypes of DLBCL samples: Activated B–Like and Germinal Centre B–Like DLBCL. Decision trees provide knowledge–based models to predict types and subtypes of DLBCL. This research suggests that the data may be insufficient to accurately predict DLBCL types or even detect functionally relevant genes. However, these methods represent reliable and understandable tools to start thinking about possible interesting non–linear interdependencies

Selecting biologically informative genes in co-expression networks with a centrality score

BACKGROUND: Measures of node centrality in biological networks are useful to detect genes with critical functional roles. In gene co-expression networks, highly connected genes (i.e., candidate hubs) have been associated with key disease-related pathways. Although different approaches to estimating gene centrality are available, their potential biological relevance in gene co-expression networks deserves further investigation. Moreover, standard measures of gene centrality focus on binary interaction networks, which may not always be suitable in the context of co-expression networks. Here, I also investigate a method that identifies potential biologically meaningful genes based on a weighted connectivity score and indicators of statistical relevance. RESULTS: The method enables a characterization of the strength and diversity of co-expression associations in the network. It outperformed standard centrality measures by highlighting more biologically informative genes in different gene co-expression networks and biological research domains. As part of the illustration of the gene selection potential of this approach, I present an application case in zebrafish heart regeneration. The proposed technique predicted genes that are significantly implicated in cellular processes required for tissue regeneration after injury. CONCLUSIONS: A method for selecting biologically informative genes from gene co-expression networks is provided, together with free open software. REVIEWERS: This article was reviewed by Anthony Almudevar, Maciej M Kańduła (nominated by David P Kreil) and Christine Wells

Integrated Ugi-Based Assembly of Functionally, Skeletally, and Stereochemically Diverse 1,4-Benzodiazepin-2-ones

A practical, integrated and versatile U-4CR-based assembly of 1,4-benzodiazepin-2-ones exhibiting functionally, skeletally, and stereochemically diverse substitution patterns is described. By virtue of its convergence, atom economy, and bond-forming efficiency, the methodology documented herein exemplifies the reconciliation of structural complexity and experimental simplicity in the context of medicinal chemistry projects.This work was financially supported by the Galician Government (Spain), Projects: 09CSA016234PR and GPC-2014-PG037. J.A. thanks FUNDAYACUCHO (Venezuela) for a predoctoral grant and Deputación da Coruña (Spain) for a postdoctoral research grant. A.N.-V. thanks the Spanish government for a Ramón y Cajal research contract

NEON terrestrial field observations: designing continental-scale, standardized sampling.

Rapid changes in climate and land use and the resulting shifts in species distributions and ecosystem functions have motivated the development of the National Ecological Observatory Network (NEON). Integrating across spatial scales from ground sampling to remote sensing, NEON will provide data for users to address ecological responses to changes in climate, land use, and species invasion across the United States for at least 30 years. Although NEON remote sensing and tower sensor elements are relatively well known, the biological measurements are not. This manuscript describes NEON terrestrial sampling, which targets organisms across a range of generation and turnover times, and a hierarchy of measurable biological states. Measurements encompass species diversity, abundance, phenology, demography, infectious disease, ecohydrology, and biogeochemistry. The continental-scale sampling requires collection of comparable and calibrated data using transparent methods. Data will be publicly available in a variety of formats and suitable for integration with other long-term efforts. NEON will provide users with the data necessary to address large-scale questions, challenge current ecological paradigms, and forecast ecological change

Stab Injury to the Preauricular Region With Laceration of the External Carotid Artery Without Involvement of the Facial Nerve: a Case Report

BACKGROUND: Open injuries to the face involving the external carotid artery are uncommon. These injuries are normally associated with laceration of the facial nerve because this nerve is more superficial than the external carotid artery. Hence, external carotid artery lesions are usually associated with facial nerve dysfunction. We present an unusual case report in which the patient had an injury to this artery with no facial nerve compromise. CASE PRESENTATION: A 25-year-old Portuguese man sustained a stab wound injury to his right preauricular region with a broken glass. Immediate profuse bleeding ensued. Provisory tamponade of the wound was achieved at the place of aggression by two off-duty doctors. He was initially transferred to a district hospital, where a large arterial bleeding was observed and a temporary compressive dressing was applied. Subsequently, the patient was transferred to a tertiary hospital. At admission in the emergency room, he presented a pulsating lesion in the right preauricular region and slight weakness in the territory of the inferior buccal branch of the facial nerve. The physical examination suggested an arterial lesion superficial to the facial nerve. However, in the operating theater, a section of the posterior and lateral flanks of the external carotid artery inside the parotid gland was identified. No lesion of the facial nerve was observed, and the external carotid artery was repaired. To better understand the anatomical rationale of this uncommon clinical case, we dissected the preauricular region of six cadavers previously injected with colored latex solutions in the vascular system. A small triangular space between the two main branches of division of the facial nerve in which the external carotid artery was not covered by the facial nerve was observed bilaterally in all cases. CONCLUSIONS: This clinical case illustrates that, in a preauricular wound, the external carotid artery can be injured without facial nerve damage. However, no similar description was found in the reviewed literature, which suggests that this must be a very rare occurrence. According to the dissection study performed, this is due to the existence of a triangular space between the cervicofacial and temporofacial nerve trunks in which the external carotid artery is not covered by the facial nerve or its branches.info:eu-repo/semantics/publishedVersio

Predictive integration of gene functional similarity and co-expression defines treatment response of endothelial progenitor cells

<p>Abstract</p> <p>Background</p> <p>Endothelial progenitor cells (EPCs) have been implicated in different processes crucial to vasculature repair, which may offer the basis for new therapeutic strategies in cardiovascular disease. Despite advances facilitated by functional genomics, there is a lack of systems-level understanding of treatment response mechanisms of EPCs. In this research we aimed to characterize the EPCs response to adenosine (Ado), a cardioprotective factor, based on the systems-level integration of gene expression data and prior functional knowledge. Specifically, we set out to identify novel biosignatures of Ado-treatment response in EPCs.</p> <p>Results</p> <p>The predictive integration of gene expression data and standardized functional similarity information enabled us to identify new treatment response biosignatures. Gene expression data originated from Ado-treated and -untreated EPCs samples, and functional similarity was estimated with Gene Ontology (GO)-based similarity information. These information sources enabled us to implement and evaluate an integrated prediction approach based on the concept of <it>k</it>-nearest neighbours learning (<it>k</it>NN). The method can be executed by expert- and data-driven input queries to guide the search for biologically meaningful biosignatures. The resulting <it>integrated kNN </it>system identified new candidate EPC biosignatures that can offer high classification performance (areas under the operating characteristic curve > 0.8). We also showed that the proposed models can outperform those discovered by standard gene expression analysis. Furthermore, we report an initial independent <it>in vitro </it>experimental follow-up, which provides additional evidence of the potential validity of the top biosignature.</p> <p>Conclusion</p> <p>Response to Ado treatment in EPCs can be accurately characterized with a new method based on the combination of gene co-expression data and GO-based similarity information. It also exploits the incorporation of human expert-driven queries as a strategy to guide the automated search for candidate biosignatures. The proposed biosignature improves the systems-level characterization of EPCs. The new integrative predictive modeling approach can also be applied to other phenotype characterization or biomarker discovery problems.</p

Coordinated modular functionality and prognostic potential of a heart failure biomarker-driven interaction network

<p>Abstract</p> <p>Background</p> <p>The identification of potentially relevant biomarkers and a deeper understanding of molecular mechanisms related to heart failure (HF) development can be enhanced by the implementation of biological network-based analyses. To support these efforts, here we report a global network of protein-protein interactions (PPIs) relevant to HF, which was characterized through integrative bioinformatic analyses of multiple sources of "omic" information.</p> <p>Results</p> <p>We found that the structural and functional architecture of this PPI network is highly modular. These network modules can be assigned to specialized processes, specific cellular regions and their functional roles tend to partially overlap. Our results suggest that HF biomarkers may be defined as key coordinators of intra- and inter-module communication. Putative biomarkers can, in general, be distinguished as "information traffic" mediators within this network. The top high traffic proteins are encoded by genes that are not highly differentially expressed across HF and non-HF patients. Nevertheless, we present evidence that the integration of expression patterns from high traffic genes may support accurate prediction of HF. We quantitatively demonstrate that intra- and inter-module functional activity may be controlled by a family of transcription factors known to be associated with the prevention of hypertrophy.</p> <p>Conclusion</p> <p>The systems-driven analysis reported here provides the basis for the identification of potentially novel biomarkers and understanding HF-related mechanisms in a more comprehensive and integrated way.</p

Metrics for GO based protein semantic similarity: a systematic evaluation

<p>Abstract</p> <p>Background</p> <p>Several semantic similarity measures have been applied to gene products annotated with Gene Ontology terms, providing a basis for their functional comparison. However, it is still unclear which is the best approach to semantic similarity in this context, since there is no conclusive evaluation of the various measures. Another issue, is whether electronic annotations should or not be used in semantic similarity calculations.</p> <p>Results</p> <p>We conducted a systematic evaluation of GO-based semantic similarity measures using the relationship with sequence similarity as a means to quantify their performance, and assessed the influence of electronic annotations by testing the measures in the presence and absence of these annotations. We verified that the relationship between semantic and sequence similarity is not linear, but can be well approximated by a rescaled Normal cumulative distribution function. Given that the majority of the semantic similarity measures capture an identical behaviour, but differ in resolution, we used the latter as the main criterion of evaluation.</p> <p>Conclusions</p> <p>This work has provided a basis for the comparison of several semantic similarity measures, and can aid researchers in choosing the most adequate measure for their work. We have found that the hybrid <it>simGIC</it> was the measure with the best overall performance, followed by Resnik's measure using a best-match average combination approach. We have also found that the average and maximum combination approaches are problematic since both are inherently influenced by the number of terms being combined. We suspect that there may be a direct influence of data circularity in the behaviour of the results including electronic annotations, as a result of functional inference from sequence similarity.</p