Annotation Propagation Research Articles

Investigation of Premyrsinane and Myrsinane Esters in Euphorbia cupanii and Euphobia pithyusa with MS2LDA and Combinatorial Molecular Network Annotation Propagation.

The species Euphorbia pithyusa and Euphorbia cupanii are two closely related Mediterranean spurges for which their taxonomic relationships are still being debated. Herein, the diterpene ester content of E. cupanii was investigated using liquid chromatography coupled to tandem mass spectrometry. The use of molecular networking coupled to unsupervised substructure annotation ( MS2LDA) indicatedthe presence of new premyrsinane/myrsinane diterpene esters in the E. cupanii fractions. A structure-guided isolation procedure yielded 16 myrsinane (11a-h, 12, and 13) and premyrsinane esters (14a-c and 15a-c), along with four 4β-phorbol esters (16a-c and 17) that showedinhibitory activity against chikungunya virus replication. The structures of the 16 new compounds (11a-c, 11h, 12, 13, 14a-c, 15a-c, 16a-c, and 17) were characterized by NMR spectroscopy and X-ray crystallography. To further uncover the diterpene ester content of these two species, the concept of combinatorial network annotation propagation (C-NAP) was developed. By leveraging the fact thatthe diterpene esters of Euphorbia species are made up of limited building blocks, a combinatorial database of theoretical structures was created and used for C-NAP that made possible the annotation of 123 premyrsinane or myrsinane esters, from which 74% are not found in any compounddatabase.

In silico annotation of discriminative markers of three Zanthoxylum species using molecular network derived annotation propagation

In liquid chromatography-mass spectrometry (LC-MS) metabolomics, data matrices with up to thousands of variables for each ion peak are subjected to multivariate analysis (MVA) to assess the homogeneity between samples. The large dimensions of LC/MS datasets hinder the identification of the discriminant or the metabolic markers. In the present study, the molecular network (MN) approach and two in silico annotation tools, network annotation propagation (NAP) and the hierarchical chemical classification method, ClassyFire, were used to annotate the metabolites of three Zanthoxylum species, Z. bungeanum, Z. schinifolium and Z. piperitum. The in silico annotation results of the MN nodes and the MVA variables were combined and visualized in loading plots. This approach helped intuitive detection of the variables that greatly contributed to the separation of the samples in the score plot as discriminant or metabolic markers, thereby allowing rapid annotation of two flavanone derivatives.

Targeted Isolation of Neuroprotective Dicoumaroyl Neolignans and Lignans from Sageretia theezans Using in Silico Molecular Network Annotation Propagation-Based Dereplication.

The integration of LC-MS/MS molecular networking and in silico MS/MS fragmentation is an emerging method for dereplication of natural products. In the present study, a targeted isolation of natural products using a new in silico-based annotation tool named Network Annotation Propagation (NAP) is described. NAP improves accuracy of in silico fragmentation analyses by reranking candidate structures based on the network topology from MS/MS-based molecular networking. Annotation for the MS/MS spectral network of the Sageratia theezans twig extract was performed using NAP, and most molecular families within the network, including the known triterpenoids 1-7, could be putatively annotated, without relying on any previous reports of molecules from this species. Based on the in silico dereplication results, molecules were prioritized for isolation. In total, six dicoumaroyl 8- O-4' neolignans (8-13) and three dicoumaroyl lignans (14-16) were isolated from the twigs of S. theezans and structurally characterized by spectroscopic analyses. Isolates were evaluated for their neuroprotective activity, and compounds 14-16 showed potent protective effects against glutamate-induced oxidative stress in mouse HT22 cells at a concentration of 12.5 μM.

Propagating annotations of molecular networks using in silico fragmentation.

The annotation of small molecules is one of the most challenging and important steps in untargeted mass spectrometry analysis, as most of our biological interpretations rely on structural annotations. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments and has been widely applied to propagate annotations. However, propagation is done through manual inspection of MS/MS spectra connected in the spectral networks and is only possible when a reference library spectrum is available. One of the alternative approaches used to annotate an unknown fragmentation mass spectrum is through the use of in silico predictions. One of the challenges of in silico annotation is the uncertainty around the correct structure among the predicted candidate lists. Here we show how molecular networking can be used to improve the accuracy of in silico predictions through propagation of structural annotations, even when there is no match to a MS/MS spectrum in spectral libraries. This is accomplished through creating a network consensus of re-ranked structural candidates using the molecular network topology and structural similarity to improve in silico annotations. The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp.

Insights into Ciliary Genes and Evolution from Multi-Level Phylogenetic Profiling.

Cilia (flagella) are important eukaryotic organelles, present in the Last Eukaryotic Common Ancestor, and are involved in cell motility and integration of extracellular signals. Ciliary dysfunction causes a class of genetic diseases, known as ciliopathies, however current knowledge of the underlying mechanisms is still limited and a better characterization of genes is needed. As cilia have been lost independently several times during evolution and they are subject to important functional variation between species, ciliary genes can be investigated through comparative genomics. We performed phylogenetic profiling by predicting orthologs of human protein-coding genes in 100 eukaryotic species. The analysis integrated three independent methods to predict a consensus set of 274 ciliary genes, including 87 new promising candidates. A fine-grained analysis of the phylogenetic profiles allowed a partitioning of ciliary genes into modules with distinct evolutionary histories and ciliary functions (assembly, movement, centriole, etc.) and thus propagation of potential annotations to previously undocumented genes. The cilia/basal body localization was experimentally confirmed for five of these previously unannotated proteins (LRRC23, LRRC34, TEX9, WDR27, and BIVM), validating the relevance of our approach. Furthermore, our multi-level analysis sheds light on the core gene sets retained in gamete-only flagellates or Ecdysozoa for instance. By combining gene-centric and species-oriented analyses, this work reveals new ciliary and ciliopathy gene candidates and provides clues about the evolution of ciliary processes in the eukaryotic domain. Additionally, the positive and negative reference gene sets and the phylogenetic profile of human genes constructed during this study can be exploited in future work.

Decorating the cloud: enabling annotation management in MapReduce

Data curation and annotation are indispensable mechanisms to a wide range of applications for capturing various types of metadata information. This metadata not only increases the data's credibility and merit, and allows end users and applications to make more informed decisions, but also enables advanced processing over the data that is not feasible otherwise. That is why annotation management has been extensively studied in the context of scientific repositories, web documents, and relational database systems. In this paper, we make the case that cloud-based applications that rely on the emerging Hadoop infrastructure are also in need for data curation and annotation and that the presence of such mechanisms in Hadoop would bring value-added capabilities to these applications. We propose the "CloudNotes" system, a full-fledged MapReduce-based annotation management engine. CloudNotes addresses several new challenges to annotation management including: (1) scalable and distributed processing of annotations over large clusters, (2) propagation of annotations under the MapReduce's blackbox execution model, and (3) annotation-driven optimizations ranging from proactive prefetching and colocation of annotations, annotation-aware task scheduling, novel shared execution strategies among the annotation jobs, and concurrency control mechanisms for annotation management. These challenges have not been addressed or explored before by the state-of-art technologies. CloudNotes is built on top of the open-source Hadoop/HDFS infrastructure and experimentally evaluated to demonstrate the practicality and scalability of its features, and the effectiveness of its optimizations under large workloads.

A provenance framework for data-dependent process analysis

A data-dependent process (DDP) models an application whose control flow is guided by a finite state machine, as well as by the state of an underlying database. DDPs are commonly found e.g., in e-commerce. In this paper we develop a framework supporting the use of provenance in static (temporal) analysis of possible DDP executions. Using provenance support, analysts can interactively test and explore the effect of hypothetical modifications to a DDP's state machine and/or to the underlying database. They can also extend the analysis to incorporate the propagation of annotations from meta-domains of interest, e.g., cost or access privileges. Toward this goal we note that the framework of semiring-based provenance was proven highly effective in fulfilling similar needs in the context of database queries. In this paper we consider novel constructions that generalize the semiring approach to the context of DDP analysis. These constructions address two interacting new challenges: (1) to combine provenance annotations for both information that resides in the database and information about external inputs (e.g., user choices), and (2) to finitely capture infinite process executions. We analyze our solution from theoretical and experimental perspectives, proving its effectiveness.

Classification of annotation semirings over containment of conjunctive queries

We study the problem of query containment of conjunctive queries over annotated databases. Annotations are typically attached to tuples and represent metadata, such as probability, multiplicity, comments, or provenance. It is usually assumed that annotations are drawn from a commutative semiring. Such databases pose new challenges in query optimization, since many related fundamental tasks, such as query containment, have to be reconsidered in the presence of propagation of annotations. We axiomatize several classes of semirings for each of which containment of conjunctive queries is equivalent to existence of a particular type of homomorphism. For each of these types, we also specify all semirings for which existence of a corresponding homomorphism is a sufficient (or necessary) condition for the containment. We develop new decision procedures for containment for some semirings which are not in any of these classes. This generalizes and systematizes previous approaches.

Towards revealing the functions of all genes in plants

The great recent progress made in identifying the molecular parts lists of organisms revealed the paucity of our understanding of what most of the parts do. In this review, we introduce computational and statistical approaches and omics data used for inferring gene function in plants, with an emphasis on network-based inference. We also discuss caveats associated with network-based function predictions such as performance assessment, annotation propagation, the guilt-by-association concept, and the meaning of hubs. Finally, we note the current limitations and possible future directions such as the need for gold standard data from several species, unified access to data and tools, quantitative comparison of data and tool quality, and high-throughput experimental validation platforms for systematic gene function elucidation in plants.

Comparative Study of Trust Modeling for Automatic Landmark Tagging

Many images uploaded to social networks are related to travel, since people consider traveling to be an important event in their life. However, a significant amount of travel images on the Internet lack proper geographical annotations or tags. In many cases, the images are tagged manually. One way to make this time-consuming manual tagging process more efficient is to propagate tags from a small set of tagged images to the larger set of untagged images automatically. In this paper, we present a system for automatic geotag propagation in images based on the similarity between image content (famous landmarks) and its context (associated geotags). In such a scenario, however, an incorrect or a spam tag can damage the integrity and reliability of the automated propagation system. Therefore, for reliable geotags propagation, we suggest adopting a user trust model based on social feedback from the users of the photo-sharing system. We compare this socially-driven approach with other user trust models via experiments and subjective testing on an image database of various famous landmarks. Results demonstrate that relying on user feedback is more efficient, since the number of propagated tags more than doubles without loss of accuracy compared to using other models or propagating without trust modeling.

Ekwiwalencja intersemiotyczna w przekładzie rysunków budowlanych

This paper focuses on intersemiotic equivalence in the process of translating construction drawings into French. Construction designs are highly codified verbovisual messages characterized by conventionalized graphic and editorial forms. They constitute mainly technical drawings based on standardized semiotic systems that are specific to different areas of the construction industry. Thus translation of construction designs involves the confrontation of two intersemiotic polysystems in accordance with the rules of intersemiotic translation. While observing those rules the translator is obliged to keep the original form of visual elements as well as to provide proper annotations in the target language in accordance with the target language discourse norms. In order to achieve this goal, the translator should exhibit a profound knowledge of both Polish and French semiotic codes pertaining to the area of construction industry.

Ekwiwalencja intersemiotyczna w przekładzie rysunków budowlanych

This paper focuses on intersemiotic equivalence in the process of translating construction drawings into French. Construction designs are highly codified verbovisual messages characterized by conventionalized graphic and editorial forms. They constitute mainly technical drawings based on standardized semiotic systems that are specific to different areas of the construction industry. Thus translation of construction designs involves the confrontation of two intersemiotic polysystems in accordance with the rules of intersemiotic translation. While observing those rules the translator is obliged to keep the original form of visual elements as well as to provide proper annotations in the target language in accordance with the target language discourse norms. In order to achieve this goal, the translator should exhibit a profound knowledge of both Polish and French semiotic codes pertaining to the area of construction industry.

A Unifying Ontology to Integrate Histological and Clinical Observations for Drug-Induced Liver Injury

Drug-induced liver injury (DILI) may present any morphologic characteristic of acute or chronic liver disease with no standardized terminology in place. Defining lexemes of DILI histopathology would allow the development of advanced knowledge discovery and data mining tools for across comparisons of publicly available information. For these purposes, a DILI ontology (DILIo) was developed by using the Unified Medical Language System tool and the standardized terminology of the Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT). The DILIo was entrained on findings of 114 US Food and Drug Administration-approved drugs by extracting all clinically DILI-related histopathologic descriptions for 1082 liver biopsy samples, which were then analyzed using the Unified Medical Language System MetaMap and subsequently mapped to the SNOMED CT. The DILIo provides a standard means to describe and organize liver injury induced by drugs, enabling comparative analysis of drugs within and across histopathologic terms. The analysis showed that flutamide, troglitazone, diclofenac, isoniazid, and tamoxifen were reported to have the most diverse histopathologic observations in liver biopsy. Necrosis, cholestasis, fatty degeneration, fibrosis, infiltrate, and hepatic necrosis were the most frequent terms used as descriptors of histopathologic features of DILI. In conclusion, DILIo entrains different algorithms for an efficient meta-analysis of published findings for an improved understanding of mechanisms and clinical characteristics of DILI.

Real web community based automatic image annotation

Automatic image annotation is a challenging problem in pattern recognition. Large annotation databases are difficult to build, and the existing models can only label small scale of image sets. In order to solve the problems with the annotation of large databases, a web community based image annotation model is proposed. Firstly, an algorithm for effectively selecting training image is proposed to delete noise images from training dataset. Secondly, a method based on weighted KNN is proposed to assign weights on each image in nearest neighbor collections, which taking into account the impacts of different images in nearest neighbor collections. By this way, training images that are more similar to unlabeled image will have higher confidences in the annotation propagation process. Thirdly, an annotation refinement method based on WordNet level is proposed to improve the annotation results of non-abstract words. Our model is appropriate for annotating images from large-scale real web community. Experiments conducted on large-scale datasets verify the effectiveness of the proposed model.

Multimedia search and retrieval using multimodal annotation propagation and indexing techniques

In this paper, a complete solution for search and retrieval of rich multimedia content over modern databases is presented. The framework proposed in this paper combines the advantages of multimodal search with those of annotation propagation into a unified system. Moreover, an effective technique, which is appropriate for large-scale indexing, is adopted, extended and integrated to the proposed framework so as to achieve optimized search and retrieval of rich media content even from large-scale databases.

On the Complexity of View Update Analysis and Its Application to Annotation Propagation

This paper investigates three problems identified in [1] for annotation propagation, namely, the view side-effect, source side-effect, and annotation placement problems. Given annotations entered for a tuple or an attribute in a view, these problems ask what tuples or attributes in the source have to be annotated to produce the view annotations. As observed in [1], these problems are fundamental not only for data provenance but also for the management of view updates. For an annotation attached to a single existing tuple in a view, it has been shown that these problems are often intractable even for views defined in terms of simple SPJU queries [1]. We revisit these problems by considering several dichotomies: (1) views defined in various subclasses of SPJU, versus SPJU views under a practical key preserving condition; (2) annotations attached to existing tuples in a view versus annotations on tuples to be inserted into the view; and (3) a single-tuple annotation versus a group of annotations. We provide a complete picture of intractability and tractability for the three problems in all these settings. We show that key preserving views often simplify the propagation analysis. Indeed, some problems become tractable for certain key preserving views, as opposed to the intractability of their counterparts that are not key preserving. However, group annotations often make the analysis harder. In addition, the problems have quite diverse complexity when annotations are attached to existing tuples in a view and when they are entered for tuples to be inserted into the view.

Video archaeology: understanding video manipulation history

Facing the explosive growth of near-duplicate videos, video archaeology is quite desired to investigate the history of the manipulations on these videos. With the determination of derived videos according to the manipulations, a video migration map can be constructed with the pair-wise relationships in a set of near-duplicate videos. In this paper, we propose an improved video archaeology (I-VA) system by extending our previous work (Shen et al. 2010). The extensions include more comprehensive video manipulation detectors and improved techniques for these detectors. Specially, the detectors are used for two categories of manipulations, i.e., semantic-based manipulations and non-semantic-based manipulations. Moreover, the improved detecting algorithms are more stable. The key of I-VA is the construction of a video migration map, which represents the history of how near-duplicate videos have been manipulated. There are various applications based on the proposed I-VA system, such as better understanding of the meaning and context conveyed by the manipulated videos, improving current video search engines by better presentation based on the migration map, and better indexing scheme based on the annotation propagation. The system is tested on a collection of 12,790 videos and 3,481 duplicates. The experimental results show that I-VA can discover the manipulation relation among the near-duplicate videos effectively.

A Multi-Directional Search technique for image annotation propagation

Image annotation has attracted lots of attention due to its importance in image understanding and search areas. In this paper, we propose a novel Multi-Directional Search framework for semi-automatic annotation propagation. In this system, the user interacts with the system to provide example images and the corresponding annotations during the annotation propagation process. In each iteration, the example images are clustered and the corresponding annotations are propagated separately to each cluster: images in the local neighborhood are annotated. Furthermore, some of those images are returned to the user for further annotation. As the user marks more images, the annotation process goes into multiple directions in the feature space. The query movements can be treated as multiple path navigation. Each path could be further split based on the user’s input. In this manner, the system provides accurate annotation assistance to the user - images with the same semantic meaning but different visual characteristics can be handled effectively. From comprehensive experiments on Corel and U. of Washington image databases, the proposed technique shows accuracy and efficiency on annotating image databases.

Phylogenetic-based propagation of functional annotations within the Gene Ontology consortium

The goal of the Gene Ontology (GO) project is to provide a uniform way to describe the functions of gene products from organisms across all kingdoms of life and thereby enable analysis of genomic data. Protein annotations are either based on experiments or predicted from protein sequences. Since most sequences have not been experimentally characterized, most available annotations need to be based on predictions. To make as accurate inferences as possible, the GO Consortium's Reference Genome Project is using an explicit evolutionary framework to infer annotations of proteins from a broad set of genomes from experimental annotations in a semi-automated manner. Most components in the pipeline, such as selection of sequences, building multiple sequence alignments and phylogenetic trees, retrieving experimental annotations and depositing inferred annotations, are fully automated. However, the most crucial step in our pipeline relies on software-assisted curation by an expert biologist. This curation tool, Phylogenetic Annotation and INference Tool (PAINT) helps curators to infer annotations among members of a protein family. PAINT allows curators to make precise assertions as to when functions were gained and lost during evolution and record the evidence (e.g. experimentally supported GO annotations and phylogenetic information including orthology) for those assertions. In this article, we describe how we use PAINT to infer protein function in a phylogenetic context with emphasis on its strengths, limitations and guidelines. We also discuss specific examples showing how PAINT annotations compare with those generated by other highly used homology-based methods.

Kernel-based semantic relation detection and classification via enriched parse tree structure

This paper proposes a tree kernel method of semantic relation detection and classification (RDC) between named entities. It resolves two critical problems in previous tree kernel methods of RDC. First, a new tree kernel is presented to better capture the inherent structural information in a parse tree by enabling the standard convolution tree kernel with context-sensitiveness and approximate matching of sub-trees. Second, an enriched parse tree structure is proposed to well derive necessary structural information, e.g., proper latent annotations, from a parse tree. Evaluation on the ACE RDC corpora shows that both the new tree kernel and the enriched parse tree structure contribute significantly to RDC and our tree kernel method much outperforms the state-of-the-art ones.