Autoantibodies refer to antibodies that target self-antigens, which can play pivotal roles in maintaining homeostasis, distinguishing normal from tumor tissue and trigger autoimmune diseases. In the last three decades, tremendous efforts have been devoted to elucidate the generation, evolution and functions of autoantibodies, as well as their target autoantigens. However, reports of these countless previously identified autoantigens are randomly dispersed in the literature. Here, we constructed an AAgAtlas database 1.0 using text-mining and manual curation. We extracted 45 830 autoantigen-related abstracts and 94 313 sentences from PubMed using the keywords of either ‘autoantigen’ or ‘autoantibody’ or their lexical variants, which were further refined to 25 520 abstracts, 43 253 sentences and 3984 candidates by our bio-entity recognizer based on the Protein Ontology. Finally, we identified 1126 genes as human autoantigens and 1071 related human diseases, with which we constructed a human autoantigen database (AAgAtlas database 1.0). The database provides a user-friendly interface to conveniently browse, retrieve and download human autoantigens as well as their associated diseases. The database is freely accessible at http://biokb.ncpsb.org/aagatlas/. We believe this database will be a valuable resource to track and understand human autoantigens as well as to investigate their functions in basic and translational research.

The Chromosome-centric Human Proteome Project (C-HPP) aims to map and annotate the entire human proteome by the "chromosome-by-chromosome" strategy. As the C-HPP proceeds, the increasing volume of proteomic data sets presents a challenge for customized and reproducible bioinformatics data analyses for mining biological knowledge. To address this challenge, we updated the previous static proteome browser CAPER into a higher version, CAPER 2.0 - an interactive, configurable and extensible workflow-based platform for C-HPP data analyses. In addition to the previous visualization functions of track-view and heatmap-view, CAPER 2.0 presents a powerful toolbox for C-HPP data analyses and also integrates a configurable workflow system that supports the view, construction, edit, run, and share of workflows. These features allow users to easily conduct their own C-HPP proteomic data analyses and visualization by CAPER 2.0. We illustrate the usage of CAPER 2.0 with four specific workflows for finding missing proteins, mapping peptides to chromosomes for genome annotation, integrating peptides with transcription factor binding sites from ENCODE data sets, and functionally annotating proteins. The updated CAPER is available at http://www.bprc.ac.cn/CAPE.

Abstract. Aiming at the difficulties to prevent Web applications to be maliciously injected which are increased by all kinds of dynamic Web technologies applied, concentrate on XSS attack, this paper reviews the research progresses of Web application injection vulnerabilities detection in recent years. It summarizes the classification and causes of the XSS injection security vulnerabilities, analyzes the complexity of security vulnerabilities detection; then proposes the key technologies of the existing detection approached, including analyzing and identifying the injection points, injection detection by software analysis and testing, symbolic execution, taint analysis; finally presents its future development direction.

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Natural products from traditional medicine inherit bioactivity from their source herbs. However, the pharmacological mechanism of natural products is often unclear and studied insufficiently. Pathway fingerprint similarity based on “drug-target-pathway” heterogeneous network provides new insight into Mechanism of Action (MoA) for natural products compared with reference drugs, which are selected approved drugs with similar bioactivity. Natural products with similar pathway fingerprints may have similar MoA to approved drugs. In our study, XYPI, an andrographolide derivative, had similar anti-inflammatory activity to Glucocorticoids (GCs) and Nonsteroidal Anti-inflammatory Drugs (NSAIDs), and GCs and NSAIDs have completely different MoA. Based on similarity evaluation, XYPI has similar pathway fingerprints as NSAIDs, but has similar target profile with GCs. The expression pattern of genes in LPS-activated macrophages after XYPI treatment is similar to that after NSAID but not GC treatment, and this experimental result is consistent with the computational prediction based on pathway fingerprints. These results imply that the pathway fingerprints of drugs have potential for drug similarity evaluation. This study used XYPI as an example to propose a new approach for investigating the pharmacological mechanism of natural products using pathway fingerprint similarity based on a “drug-target-pathway” heterogeneous network.