SmartR: An open-source platform for interactive visual analytics for translational research data.

in Bioinformatics (2017)

In translational research, efficient knowledge exchange between the different fields of expertise is crucial. An open platform that is capable of storing a multitude of data types such as clinical, pre ... [more ▼]

In translational research, efficient knowledge exchange between the different fields of expertise is crucial. An open platform that is capable of storing a multitude of data types such as clinical, pre-clinical, or OMICS data combined with strong visual analytical capabilities will significantly accelerate the scientific progress by making data more accessible and hypothesis generation easier. The open data warehouse tranSMART is capable of storing a variety of data types and has a growing user community including both academic institutions and pharmaceutical companies. tranSMART, however, currently lacks interactive and dynamic visual analytics and does not permit any post-processing interaction or exploration. For this reason, we developed SmartR , a plugin for tranSMART, that equips the platform not only with several dynamic visual analytical workflows, but also provides its own framework for the addition of new custom workflows. Modern web technologies such as D3.js or AngularJS were used to build a set of standard visualizations that were heavily improved with dynamic elements. Contact: reinhard.schneider@uni.lu. Supplementary information: Supplementary data are available at Bioinformatics online. Availability: : The source code is licensed under the Apache 2.0 License and is freely available on GitHub: https://github.com/transmart/SmartR. [less ▲]

uORFdb--a comprehensive literature database on eukaryotic uORF biology.

in Nucleic acids research (2014), 42(1), 60-7

Approximately half of all human transcripts contain at least one upstream translational initiation site that precedes the main coding sequence (CDS) and gives rise to an upstream open reading frame (uORF ... [more ▼]

Approximately half of all human transcripts contain at least one upstream translational initiation site that precedes the main coding sequence (CDS) and gives rise to an upstream open reading frame (uORF). We generated uORFdb, publicly available at http://cbdm.mdc-berlin.de/tools/uorfdb, to serve as a comprehensive literature database on eukaryotic uORF biology. Upstream ORFs affect downstream translation by interfering with the unrestrained progression of ribosomes across the transcript leader sequence. Although the first uORF-related translational activity was observed >30 years ago, and an increasing number of studies link defective uORF-mediated translational control to the development of human diseases, the features that determine uORF-mediated regulation of downstream translation are not well understood. The uORFdb was manually curated from all uORF-related literature listed at the PubMed database. It categorizes individual publications by a variety of denominators including taxon, gene and type of study. Furthermore, the database can be filtered for multiple structural and functional uORF-related properties to allow convenient and targeted access to the complex field of eukaryotic uORF biology. [less ▲]

Genie: literature-based gene prioritization at multi genomic scale.

in Nucleic acids research (2011), 39(Web Server issue), 455-61

Biomedical literature is traditionally used as a way to inform scientists of the relevance of genes in relation to a research topic. However many genes, especially from poorly studied organisms, are not ... [more ▼]

Biomedical literature is traditionally used as a way to inform scientists of the relevance of genes in relation to a research topic. However many genes, especially from poorly studied organisms, are not discussed in the literature. Moreover, a manual and comprehensive summarization of the literature attached to the genes of an organism is in general impossible due to the high number of genes and abstracts involved. We introduce the novel Genie algorithm that overcomes these problems by evaluating the literature attached to all genes in a genome and to their orthologs according to a selected topic. Genie showed high precision (up to 100%) and the best performance in comparison to other algorithms in most of the benchmarks, especially when high sensitivity was required. Moreover, the prioritization of zebrafish genes involved in heart development, using human and mouse orthologs, showed high enrichment in differentially expressed genes from microarray experiments. The Genie web server supports hundreds of species, millions of genes and offers novel functionalities. Common run times below a minute, even when analyzing the human genome with hundreds of thousands of literature records, allows the use of Genie in routine lab work. Availability: http://cbdm.mdc-berlin.de/tools/genie/. [less ▲]

LAITOR - Literature Assistant for Identification of Terms co-Occurrences and Relationships.

in BMC Bioinformatics (2010), 11

BACKGROUND: Biological knowledge is represented in scientific literature that often describes the function of genes/proteins (bioentities) in terms of their interactions (biointeractions). Such ... [more ▼]

BACKGROUND: Biological knowledge is represented in scientific literature that often describes the function of genes/proteins (bioentities) in terms of their interactions (biointeractions). Such bioentities are often related to biological concepts of interest that are specific of a determined research field. Therefore, the study of the current literature about a selected topic deposited in public databases, facilitates the generation of novel hypotheses associating a set of bioentities to a common context. RESULTS: We created a text mining system (LAITOR: Literature Assistant for Identification of Terms co-Occurrences and Relationships) that analyses co-occurrences of bioentities, biointeractions, and other biological terms in MEDLINE abstracts. The method accounts for the position of the co-occurring terms within sentences or abstracts. The system detected abstracts mentioning protein-protein interactions in a standard test (BioCreative II IAS test data) with a precision of 0.82-0.89 and a recall of 0.48-0.70. We illustrate the application of LAITOR to the detection of plant response genes in a dataset of 1000 abstracts relevant to the topic. CONCLUSIONS: Text mining tools combining the extraction of interacting bioentities and biological concepts with network displays can be helpful in developing reasonable hypotheses in different scientific backgrounds. [less ▲]

A reference guide for tree analysis and visualization

in BioData Mining (2010), 3(1), 1

The quantities of data obtained by the new high-throughput technologies, such as microarrays or ChIP-Chip arrays, and the large-scale OMICS-approaches, such as genomics, proteomics and transcriptomics ... [more ▼]

The quantities of data obtained by the new high-throughput technologies, such as microarrays or ChIP-Chip arrays, and the large-scale OMICS-approaches, such as genomics, proteomics and transcriptomics, are becoming vast. Sequencing technologies become cheaper and easier to use and, thus, large-scale evolutionary studies towards the origins of life for all species and their evolution becomes more and more challenging. Databases holding information about how data are related and how they are hierarchically organized expand rapidly. Clustering analysis is becoming more and more difficult to be applied on very large amounts of data since the results of these algorithms cannot be efficiently visualized. Most of the available visualization tools that are able to represent such hierarchies, project data in 2D and are lacking often the necessary user friendliness and interactivity. For example, the current phylogenetic tree visualization tools are not able to display easy to understand large scale trees with more than a few thousand nodes. In this study, we review tools that are currently available for the visualization of biological trees and analysis, mainly developed during the last decade. We describe the uniform and standard computer readable formats to represent tree hierarchies and we comment on the functionality and the limitations of these tools. We also discuss on how these tools can be developed further and should become integrated with various data sources. Here we focus on freely available software that offers to the users various tree-representation methodologies for biological data analysis. [less ▲]

Clustering of cognate proteins among distinct proteomes derived from multiple links to a single seed sequence.

in BMC bioinformatics (2008), 9

BACKGROUND: Modern proteomes evolved by modification of pre-existing ones. It is extremely important to comparative biology that related proteins be identified as members of the same cognate group, since ... [more ▼]

BACKGROUND: Modern proteomes evolved by modification of pre-existing ones. It is extremely important to comparative biology that related proteins be identified as members of the same cognate group, since a characterized putative homolog could be used to find clues about the function of uncharacterized proteins from the same group. Typically, databases of related proteins focus on those from completely-sequenced genomes. Unfortunately, relatively few organisms have had their genomes fully sequenced; accordingly, many proteins are ignored by the currently available databases of cognate proteins, despite the high amount of important genes that are functionally described only for these incomplete proteomes. RESULTS: We have developed a method to cluster cognate proteins from multiple organisms beginning with only one sequence, through connectivity saturation with that Seed sequence. We show that the generated clusters are in agreement with some other approaches based on full genome comparison. CONCLUSION: The method produced results that are as reliable as those produced by conventional clustering approaches. Generating clusters based only on individual proteins of interest is less time consuming than generating clusters for whole proteomes. [less ▲]

Development of SRS.php, a Simple Object Access Protocol-based library for data acquisition from integrated biological databases.

in Genetics and Molecular Research (2007), 6(4), 1142-1150

Data integration has become an important task for biological database providers. The current model for data exchange among different sources simplifies the manner that distinct information is accessed by ... [more ▼]

Data integration has become an important task for biological database providers. The current model for data exchange among different sources simplifies the manner that distinct information is accessed by users. The evolution of data representation from HTML to XML enabled programs, instead of humans, to interact with biological databases. We present here SRS.php, a PHP library that can interact with the data integration Sequence Retrieval System (SRS). The library has been written using SOAP definitions, and permits the programmatic communication through webservices with the SRS. The interactions are possible by invoking the methods described in WSDL by exchanging XML messages. The current functions available in the library have been built to access specific data stored in any of the 90 different databases (such as UNIPROT, KEGG and GO) using the same query syntax format. The inclusion of the described functions in the source of scripts written in PHP enables them as webservice clients to the SRS server. The functions permit one to query the whole content of any SRS database, to list specific records in these databases, to get specific fields from the records, and to link any record among any pair of linked databases. The case study presented exemplifies the library usage to retrieve information regarding registries of a Plant Defense Mechanisms database. The Plant Defense Mechanisms database is currently being developed, and the proposal of SRS.php library usage is to enable the data acquisition for the further warehousing tasks related to its setup and maintenance. [less ▲]

Moving pieces in a taxonomic puzzle: venom 2D-LC/MS and data clustering analyses to infer phylogenetic relationships in some scorpions from the Buthidae family (Scorpiones).

in Toxicon : official journal of the International Society on Toxinology (2006), 47(6), 628-39

The Buthidae is the most clinically important scorpion family, with over 500 species distributed worldwide. Taxonomical positions and phylogenetic relationships concerning the representative genera and ... [more ▼]

The Buthidae is the most clinically important scorpion family, with over 500 species distributed worldwide. Taxonomical positions and phylogenetic relationships concerning the representative genera and species of this family have been mostly inferred based upon comparisons between morphological characters. Yet, some authors have performed such inferences by comparing some structural properties of a few selected molecules found in the venoms from these scorpions. Here, we propose a novel methodology pipeline designed to address these issues. We have analyzed the whole venoms from some species that exemplify peculiar cases in the Buthidae family (Tityus stigmurus, Tityus serrulatus, Tityus bahiensis, Leiurus quinquestriatus quinquestriatus and Leiurus quinquestriatus hebraeus), by means of a proteomic approach using a 2D-LC/MS technique. The molecules found in these venoms were clustered according to their physicochemical properties (molecular mass and hydrophobicity), by using the machine learning-based Weka software. The clusters assessment, along with the number of molecules found in a given cluster for each scorpion, which assigns for the venom and structural family complexities, respectively, was used to generate a phenetic correlation tree for positioning these species. Our results were in accordance with the classical taxonomy viewpoint, which places T. serrulatus and T. stigmurus as very close species, T. bahiensis as a less related species in the Tityus genus and L. q. quinquestriatus and L. q. hebraeus with small differences within the same species (L. quinquestriatus). Therefore, we believe that this is a well-suited method to determine venom complexities that reflect the scorpions' evolutionary history, which can be crucial to reconstruct their phylogeny through the molecular evolution of their venoms. [less ▲]