Domain selection combined with improved cloning strategy for high throughput expression of higher eukaryotic proteins

Background  

Expression of higher eukaryotic genes as soluble, stable recombinant proteins is still a bottleneck step in biochemical and structural studies of novel proteins today. Correct identification of stable domains/fragments within the open reading frame (ORF), combined with proper cloning strategies, can greatly enhance the success rate when higher eukaryotic proteins are expressed as these domains/fragments. Furthermore, a HTP cloning pipeline incorporated with bioinformatics domain/fragment selection methods will be beneficial to studies of structure and function genomics/proteomics.     

Atlas – a data warehouse for integrative bioinformatics

Background  

We present a biological data warehouse called Atlas that locally stores and integrates biological sequences, molecular interactions, homology information, functional annotations of genes, and biological ontologies. The goal of the system is to provide data, as well as a software infrastructure for bioinformatics research and development.     

Integrating sequence and structural biology with DAS

Background  

The Distributed Annotation System (DAS) is a network protocol for exchanging biological data. It is frequently used to share annotations of genomes and protein sequence.     

DWARF – a data warehouse system for analyzing protein families

Background  

The emerging field of integrative bioinformatics provides the tools to organize and systematically analyze vast amounts of highly diverse biological data and thus allows to gain a novel understanding of complex biological systems. The data warehouse DWARF applies integrative bioinformatics approaches to the analysis of large protein families.     

MetNetGE: interactive views of biological networks and ontologies

Background  

Linking high-throughput experimental data with biological networks is a key step for understanding complex biological systems. Currently, visualization tools for large metabolic networks often result in a dense web of connections that is difficult to interpret biologically. The MetNetGE application organizes and visualizes biological networks in a meaningful way to improve performance and biological interpretability.     

easyDAS: Automatic creation of DAS servers

Background  

The Distributed Annotation System (DAS) has proven to be a successful way to publish and share biological data. Although there are more than 750 active registered servers from around 50 organizations, setting up a DAS server comprises a fair amount of work, making it difficult for many research groups to share their biological annotations. Given the clear advantage that the generalized sharing of relevant biological data is for the research community it would be desirable to facilitate the sharing process.     

PAGE: Parametric Analysis of Gene Set Enrichment

Background  

Gene set enrichment analysis (GSEA) is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes in microarray data sets. GSEA is especially useful when gene expression changes in a given microarray data set is minimal or moderate.     

<Emphasis Type="Italic">ClustalXeed</Emphasis>: a GUI-based grid computation version for high performance and terabyte size multiple sequence alignment

Background  

There is an increasing demand to assemble and align large-scale biological sequence data sets. The commonly used multiple sequence alignment programs are still limited in their ability to handle very large amounts of sequences because the system lacks a scalable high-performance computing (HPC) environment with a greatly extended data storage capacity.     

K-OPLS package: Kernel-based orthogonal projections to latent structures for prediction and interpretation in feature space

Background  

Kernel-based classification and regression methods have been successfully applied to modelling a wide variety of biological data. The Kernel-based Orthogonal Projections to Latent Structures (K-OPLS) method offers unique properties facilitating separate modelling of predictive variation and structured noise in the feature space. While providing prediction results similar to other kernel-based methods, K-OPLS features enhanced interpretational capabilities; allowing detection of unanticipated systematic variation in the data such as instrumental drift, batch variability or unexpected biological variation.     

Using mechanistic Bayesian networks to identify downstream targets of the Sonic Hedgehog pathway

Background  

The topology of a biological pathway provides clues as to how a pathway operates, but rationally using this topology information with observed gene expression data remains a challenge.     

Genoviz Software Development Kit: Java tool kit for building genomics visualization applications

Background  

Visualization software can expose previously undiscovered patterns in genomic data and advance biological science.     

Storing,linking, and mining microarray databases using SRS

Background  

SRS (Sequence Retrieval System) has proven to be a valuable platform for storing, linking, and querying biological databases. Due to the availability of a broad range of different scientific databases in SRS, it has become a useful platform to incorporate and mine microarray data to facilitate the analyses of biological questions and non-hypothesis driven quests. Here we report various solutions and tools for integrating and mining annotated expression data in SRS.     

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.     

PubMatrix: a tool for multiplex literature mining

Background  

Molecular experiments using multiplex strategies such as cDNA microarrays or proteomic approaches generate large datasets requiring biological interpretation. Text based data mining tools have recently been developed to query large biological datasets of this type of data. PubMatrix is a web-based tool that allows simple text based mining of the NCBI literature search service PubMed using any two lists of keywords terms, resulting in a frequency matrix of term co-occurrence.     

The Longhorn Array Database (LAD): An Open-Source,MIAME compliant implementation of the Stanford Microarray Database (SMD)

Background  

The power of microarray analysis can be realized only if data is systematically archived and linked to biological annotations as well as analysis algorithms.     

MEMOSys: Bioinformatics platform for genome-scale metabolic models

Background  

Recent advances in genomic sequencing have enabled the use of genome sequencing in standard biological and biotechnological research projects. The challenge is how to integrate the large amount of data in order to gain novel biological insights. One way to leverage sequence data is to use genome-scale metabolic models. We have therefore designed and implemented a bioinformatics platform which supports the development of such metabolic models.     

MIMAS: an innovative tool for network-based high density oligonucleotide microarray data management and annotation

Background  

The high-density oligonucleotide microarray (GeneChip) is an important tool for molecular biological research aiming at large-scale detection of small nucleotide polymorphisms in DNA and genome-wide analysis of mRNA concentrations. Local array data management solutions are instrumental for efficient processing of the results and for subsequent uploading of data and annotations to a global certified data repository at the EBI (ArrayExpress) or the NCBI (GeneOmnibus).     

Life cycle assessment of Chinese radial passenger vehicle tire

Purpose

We evaluated and quantified the environmental impact of a radial tire product for passenger vehicles throughout the product’s life cycle to identify key stages that contribute to the overall environmental burden and to find ways to reduce these burdens effectively. The study covers all relevant life cycle stages, from the acquisition of raw materials to the production, use, and end of life.

Methods

Data collected onsite in 2014 by one of the largest Chinese tire companies were used in the assessment. The evaluation is presented in terms of individual impact category according to the CML model. Five impact categories (i.e., global warming potential (GWP), acidification potential (AP), photochemical oxidant creation potential (POCP), eutrophication potential (EP), and human toxicity potential (HTP)) were considered. The research was conducted in accordance with the ISO 14040/14044 standards.

Results and discussion

Fuel (gasoline) consumption represents an important contribution to most impact categories, including the GWP, AP, POCP, and EP, during the use stage. The largest contributor to the HTP category is raw material acquisition, mainly because of the impact of the production of organic chemicals. In the end-of-life stage, assuming that 100 % of used tires are collected and recycled to produce reclaimed rubber, the GWP, EP, and HTP contributions are negative, whereas those to the AP and POCP are positive. During the raw material acquisition stage, natural rubber, synthetic rubber, carbon black, and organic chemicals represent the largest contribution to the environmental impact categories. During the production stage, the compound blending process is the largest contributor to the AP and POCP, whereas vulcanizing and testing contribute most to the GWP, EP, and HTP.

Conclusions

Vehicle fuel consumption and its proportion consumed by the tires during the use stage are key factors that contribute to environmental impact during tire life. Further investigations should be conducted to decrease the impact of these factors and improve the environmental performance of tire products.

     

IntNetDB v1.0: an integrated protein-protein interaction network database generated by a probabilistic model

Background  

Although protein-protein interaction (PPI) networks have been explored by various experimental methods, the maps so built are still limited in coverage and accuracy. To further expand the PPI network and to extract more accurate information from existing maps, studies have been carried out to integrate various types of functional relationship data. A frequently updated database of computationally analyzed potential PPIs to provide biological researchers with rapid and easy access to analyze original data as a biological network is still lacking.     

Principal components analysis based methodology to identify differentially expressed genes in time-course microarray data

Background  

Time-course microarray experiments are being increasingly used to characterize dynamic biological processes. In these experiments, the goal is to identify genes differentially expressed in time-course data, measured between different biological conditions. These differentially expressed genes can reveal the changes in biological process due to the change in condition which is essential to understand differences in dynamics.