Functional Analysis beyond Enrichment: Non-Redundant Reciprocal Linkage of Genes and Biological Terms

Functional analysis of large sets of genes and proteins is becoming more and more necessary with the increase of experimental biomolecular data at omic-scale. Enrichment analysis is by far the most popular available methodology to derive functional implications of sets of cooperating genes. The problem with these techniques relies in the redundancy of resulting information, that in most cases generate lots of trivial results with high risk to mask the reality of key biological events. We present and describe a computational method, called GeneTerm Linker, that filters and links enriched output data identifying sets of associated genes and terms, producing metagroups of coherent biological significance. The method uses fuzzy reciprocal linkage between genes and terms to unravel their functional convergence and associations. The algorithm is tested with a small set of well known interacting proteins from yeast and with a large collection of reference sets from three heterogeneous resources: multiprotein complexes (CORUM), cellular pathways (SGD) and human diseases (OMIM). Statistical Precision, Recall and balanced F-score are calculated showing robust results, even when different levels of random noise are included in the test sets. Although we could not find an equivalent method, we present a comparative analysis with a widely used method that combines enrichment and functional annotation clustering. A web application to use the method here proposed is provided at http://gtlinker.cnb.csic.es

Advancements in Three-Phase Electric Motor Control: The Dual Voltag Motor Controller for Seamless Voltage Switching and Enhanced Efficiency

The primary objective of this research was to create, manufacture, and assess the operational efficiency of a Dual Voltage Motor Controller capable of automatically detecting the source voltage in a three-phase system and regulating the electric motor to function with either 220V or 440V AC. The resulting technology comprises a combination of magnetic contactors and a microcontroller, serving as a switching mechanism that streamlines the reconfiguration of the electric motor's twelve leads in a delta-delta configuration. This research was conducted at Guimaras State University, focusing on the development of a device aimed at eliminating the need for rewiring motor terminals when switching between 220V AC and 440V AC power sources, and vice versa. The device is designed exclusively for operation within a three-phase system and for electric motors utilizing a delta-delta configuration with twelve leads. Upon assessing the results of the technical evaluation, it was evident that the Dual Voltage Motor Controller effectively managed to switch the electric motor between 220V and 440V alternating current. Furthermore, the data revealed that the device allowed the electric motor to operate in both forward and reverse rotations, whether under low or high voltage conditions. By introducing this innovative technology, the research effectively resolved the limitations of existing motor controllers by introducing auto-detection of the source voltage and facilitating the seamless transfer of terminal connections via magnetic contactors. According to the feedback from technical experts, there is potential for expanding the device's applicability beyond delta-delta connected motors to also encompass wye-delta starting and running configurations for three-phase alternating current motors

MARQ: an online tool to mine GEO for experiments with similar or opposite gene expression signatures

The enormous amount of data available in public gene expression repositories such as Gene Expression Omnibus (GEO) offers an inestimable resource to explore gene expression programs across several organisms and conditions. This information can be used to discover experiments that induce similar or opposite gene expression patterns to a given query, which in turn may lead to the discovery of new relationships among diseases, drugs or pathways, as well as the generation of new hypotheses. In this work, we present MARQ, a web-based application that allows researchers to compare a query set of genes, e.g. a set of over- and under-expressed genes, against a signature database built from GEO datasets for different organisms and platforms. MARQ offers an easy-to-use and integrated environment to mine GEO, in order to identify conditions that induce similar or opposite gene expression patterns to a given experimental condition. MARQ also includes additional functionalities for the exploration of the results, including a meta-analysis pipeline to find genes that are differentially expressed across different experiments. The application is freely available at http://marq.dacya.ucm.es

Plant virus evolution under strong drought conditions results in a transition from parasitism to mutualism

Environmental conditions are an important factor driving pathogens’ evolution. Here, we explore the effects of drought stress in plant virus evolution. We evolved turnip mosaic potyvirus in well-watered and drought conditions in Arabidopsis thaliana accessions that differ in their response to virus infection. Virus adaptation occurred in all accessions independently of watering status. Drought-evolved viruses conferred a significantly higher drought tolerance to infected plants. By contrast, nonsignificant increases in tolerance were observed in plants infected with viruses evolved under standard watering. The magnitude of this effect was dependent on the plant accessions. Differences in tolerance were correlated to alterations in the expression of host genes, some involved in regulation of the circadian clock, as well as in deep changes in the balance of phytohormones regulating defense and growth signaling pathways. Our results show that viruses can promote host survival in situations of abiotic stress, with the magnitude of such benefit being a selectable trait

LLM3D: a log-linear modeling-based method to predict functional gene regulatory interactions from genome-wide expression data

All cellular processes are regulated by condition-specific and time-dependent interactions between transcription factors and their target genes. While in simple organisms, e.g. bacteria and yeast, a large amount of experimental data is available to support functional transcription regulatory interactions, in mammalian systems reconstruction of gene regulatory networks still heavily depends on the accurate prediction of transcription factor binding sites. Here, we present a new method, log-linear modeling of 3D contingency tables (LLM3D), to predict functional transcription factor binding sites. LLM3D combines gene expression data, gene ontology annotation and computationally predicted transcription factor binding sites in a single statistical analysis, and offers a methodological improvement over existing enrichment-based methods. We show that LLM3D successfully identifies novel transcriptional regulators of the yeast metabolic cycle, and correctly predicts key regulators of mouse embryonic stem cell self-renewal more accurately than existing enrichment-based methods. Moreover, in a clinically relevant in vivo injury model of mammalian neurons, LLM3D identified peroxisome proliferator-activated receptor γ (PPARγ) as a neuron-intrinsic transcriptional regulator of regenerative axon growth. In conclusion, LLM3D provides a significant improvement over existing methods in predicting functional transcription regulatory interactions in the absence of experimental transcription factor binding data

Babelomics: an integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling

Babelomics is a response to the growing necessity of integrating and analyzing different types of genomic data in an environment that allows an easy functional interpretation of the results. Babelomics includes a complete suite of methods for the analysis of gene expression data that include normalization (covering most commercial platforms), pre-processing, differential gene expression (case-controls, multiclass, survival or continuous values), predictors, clustering; large-scale genotyping assays (case controls and TDTs, and allows population stratification analysis and correction). All these genomic data analysis facilities are integrated and connected to multiple options for the functional interpretation of the experiments. Different methods of functional enrichment or gene set enrichment can be used to understand the functional basis of the experiment analyzed. Many sources of biological information, which include functional (GO, KEGG, Biocarta, Reactome, etc.), regulatory (Transfac, Jaspar, ORegAnno, miRNAs, etc.), text-mining or protein–protein interaction modules can be used for this purpose. Finally a tool for the de novo functional annotation of sequences has been included in the system. This provides support for the functional analysis of non-model species. Mirrors of Babelomics or command line execution of their individual components are now possible. Babelomics is available at http://www.babelomics.org

Interfaz Móvil de una Aplicación Sensible al Contexto Utilizando Base de Datos Difusas

La forma como los seres humanos se comunican depende del contexto, determinado por el medio que lo rodea, la percepción de cada individuo y a factores personales intrínsecos. Este tipo de comunicación no se puede trasladar directamente a los sistemas tradicionales ya que se debe proporcionar explícitamente, es decir, el contexto es preestablecido por el diseñador del sistema. Esta es la razón por la que la mayor parte del contenido que éstos retornan no está personalizado. En la actualidad, se requiere desarrollar sistemas inteligentes sensibles al contexto añadiendo nuevas funcionalidades: la posibilidad de representar información imperfecta (imprecisa, incierta o vaga), así como consultar bases de datos utilizando etiquetas lingüísticas permitiendo aproximarse al lenguaje natural humano. Estas funcionalidades se pueden añadir utilizando bases de datos difusas. El desarrollo de sistemas personalizados permitirá filtrar la gran cantidad de información proporcionada debido a los avances en las Tecnologías de Información y Comunicación. Por otra parte, el uso de dispositivos móviles está aumentando considerablemente. Por estas razones, en este trabajo se presenta el desarrollo de un prototipo de interfaz móvil para una aplicación web sensible al contexto utilizando bases de datos difusas, donde cada usuario obtiene respuestas con valores personalizados de acuerdo a sus definiciones de etiquetas lingüísticas

Pascual-Montano: Finding Closed Frequent Item Sets by Intersecting Transactions. EDBT

Most known frequent item set mining algorithms work by enumerating candidate item sets and pruning infrequent candidates. An alternative method, which works by intersecting transactions, is much less researched. To the best of our knowledge, there are only two basic algorithms: a cumulative scheme, which is based on a repository with which new transactions are intersected, and the Carpenter algorithm, which enumerates and intersects candidate transaction sets. These approaches yield the set of so-called closed frequent item sets, since any such item set can be represented as the intersection of some subset of the given transactions. In this paper we describe a considerably improved implementation scheme of the cumulative approach, which relies on a prefix tree representation of the already found intersections. In addition, we present an improved way of implementing the Carpenter algorithm. We demonstrate that on specific data sets, which occur particularly often in the area of gene expression analysis, our implementations significantly outperform enumeration approaches to frequent item set mining