抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.

/pdf/bioinformatics-enrichment-tools-paths-toward-the-2yo1xl3r2j.pdf

Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

Feature selection techniques have become an apparent need in many bioinformatics applications. In addition to the large pool of techniques that have already been developed in the machine learning and data mining fields, specific applications in bioinformatics have led to a wealth of newly proposed techniques.

In this article, we make the interested reader aware of the possibilities of feature selection, providing a basic taxonomy of feature selection techniques, and discussing their use, variety and potential in a number of both common as well as upcoming bioinformatics applications.

Contact: yvan.saeys@psb.ugent.be

Supplementary information: http://bioinformatics.psb.ugent.be/supplementary_data/yvsae/fsreview

A review of feature selection techniques in bioinformatics

Since the inception of the GO annotation project, a variety of tools have been developed that support exploring and searching the GO database In particular, a variety of tools that perform GO enrichment analysis are currently available Most of these tools require as input a target set of genes and a background set and seek enrichment in the target set compared to the background set A few tools also exist that support analyzing ranked lists The latter typically rely on simulations or on union-bound correction for assigning statistical significance to the results GOrilla is a web-based application that identifies enriched GO terms in ranked lists of genes, without requiring the user to provide explicit target and background sets This is particularly useful in many typical cases where genomic data may be naturally represented as a ranked list of genes (eg by level of expression or of differential expression) GOrilla employs a flexible threshold statistical approach to discover GO terms that are significantly enriched at the top of a ranked gene list Building on a complete theoretical characterization of the underlying distribution, called mHG, GOrilla computes an exact p-value for the observed enrichment, taking threshold multiple testing into account without the need for simulations This enables rigorous statistical analysis of thousand of genes and thousands of GO terms in order of seconds The output of the enrichment analysis is visualized as a hierarchical structure, providing a clear view of the relations between enriched GO terms GOrilla is an efficient GO analysis tool with unique features that make a useful addition to the existing repertoire of GO enrichment tools GOrilla's unique features and advantages over other threshold free enrichment tools include rigorous statistics, fast running time and an effective graphical representation GOrilla is publicly available at: http://cbl-gorillacstechnionacil

https://link.springer.com/content/pdf/10.1186%2F1471-2105-10-48.pdf

GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists

Planobispora rosea is the natural producer of the potent thiopeptide antibiotic GE2270A. Here, we present the results of a metabolomics and transcriptomics analysis of P. rosea during production of GE2270A. The data generated provides useful insights into the biology of this genetically intractable bacterium. We characterize the details of the shutdown of protein biosynthesis and the respiratory chain associated with the end of the exponential growth phase. We also provide the first description of the phosphate regulon in P. rosea. Based on the transcriptomics data, we show that both phosphate and iron are limiting P. rosea growth in our experimental conditions. Additionally, we identified and validated a new biosynthetic gene cluster associated with the production of the siderophores benarthin and dibenarthin in P. rosea. Together, the metabolomics and transcriptomics data are used to inform and refine the very first genome-scale metabolic model for P. rosea, which will be a valuable framework for the interpretation of future studies of the biology of this interesting but poorly characterized species. IMPORTANCE Planobispora rosea is a genetically intractable bacterium used for the production of GE2270A on an industrial scale. GE2270A is a potent thiopeptide antibiotic currently used as a precursor for the synthesis of two compounds under clinical studies for the treatment of Clostridium difficile infection and acne. Here, we present the very first systematic multi-omics investigation of this important bacterium, which provides a much-needed detailed picture of the dynamics of metabolism of P. rosea while producing GE2270A.

Multi-omics Study of Planobispora rosea, Producer of the Thiopeptide Antibiotic GE2270A.

Erratum to: Towards an unbiased metabolic profiling of protozoan parasites: optimisation of a Leishmania sampling protocol for HILIC-orbitrap analysis

/pdf/towards-an-unbiased-metabolic-profiling-of-protozoan-f08icj3cp9.pdf

Towards an unbiased metabolic profiling of protozoan parasites: optimisation of a Leishmania sampling protocol for HILIC-orbitrap analysis (vol 398, pg 2059, 2010)

The recent accumulation of increasingly densely sampled phylogenetic analyses of spiders has greatly advanced our understanding of evolutionary relationships within this group. Here, this diverse literature is reviewed and combined with earlier morphological analyses in an attempt to reconstruct the first fully resolved phylogeny for the spider fauna of the British Isles. The resulting tree highlights parts of the group where data are still too limited for a confident assessment of relationships, proposes a number of deviations from previously suggested phylogenetic hypotheses, and can serve as a framework for evolutionary and ecological interpretations of the biology of British spiders, as well as a starting point for future studies on a larger geographical scale.

Rainer Breitling

Papers

Multi-omics Study of Planobispora rosea, Producer of the Thiopeptide Antibiotic GE2270A.

Towards an unbiased metabolic profiling of protozoan parasites: optimisation of a Leishmania sampling protocol for HILIC-orbitrap analysis (vol 398, pg 2059, 2010)

A completely resolved phylogenetic tree of British spiders (Arachnida: Araneae)

Bayesian Approaches for Mass Spectrometry‐Based Metabolomics

Edward Alfred Heath FLS (1839–1907): homoeopath, amateur naturalist and beetle collector