A visual exploration workflow as enabler for the exploitation of Linked Open Data

Abstract. Semantically annotating and interlinking Open Data results in Linked Open Data which concisely and unambiguously describes a knowledge domain. However, the uptake of the Linked Data depends on its usefulness to non-Semantic Web experts. Failing to support data consumers to understand the added-value of Linked Data and possible exploitation opportunities could inhibit its diffusion. In this paper, we propose an interactive visual workflow for discovering and ex-ploring Linked Open Data. We implemented the workflow considering academic library metadata and carried out a qualitative evaluation. We assessed the work-flow’s potential impact on data consumers which bridges the offer: published Linked Open Data; and the demand as requests for: (i) higher quality data; and (ii) more applications that re-use data. More than 70 % of the 34 test users agreed that the workflow fulfills its goal: it facilitates non-Semantic Web experts to un-derstand the potential of Linked Open Data.

Social semantic search : a case study on web 2.0 for science

When researchers formulate search queries to find relevant content on the Web, those queries typically consist of keywords that can only be matched in the content or its metadata. The Web of Data extends this functionality by bringing structure and giving well-defined meaning to the content and it enables humans and machines to work together using controlled vocabularies. Due the high degree of mismatches between the structure of the content and the vocabularies in different sources, searching over multiple heterogeneous repositories of structured data is considered challenging. Therefore, the authors present a semantic search engine for researchers facilitating search in research related Linked Data. To facilitate high-precision interactive search, they annotated and interlinked structured research data with ontologies from various repositories in an effective semantic model. Furthermore, the authors' system is adaptive as researchers can synchronize using new social media accounts and efficiently explore new datasets

Connected innovation: an international comparative study that identifies mixed modes of innovation

This paper offers a new angle on innovation modalities by adopting a recently emerging approach towards identifying innovation typologies via exploratory data analysis techniques with the aim to tease out some underlying latent variables that represent coherent innovation strategies for groups of firms. Mixed modes of innovation include aspects of both user and open innovation, and are employed to inform on such concepts. The modes of innovation are developed by exploring micro-level innovation survey data across 18 countries. The contributions of the paper lie in (a) the identification of five core innovation modes that are found in almost all countries; and (b) examining – via regression analysis – the role of different modes in firm performance

Computational Molecular Docking Studies of Small Molecule Inhibitors With the SARS-CoV-2 Spike Protein Variants: In-Silico Drug Discovery Using Virtual Screening and Drug Repurposing Approaches

The pandemic caused by the emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019 has caused a global public health crisis of nearly unprecedented scale. In the years following the outbreak, the scientific community has mobilized to develop several vaccines and treatments. Drug repurposing as a strategy for drug development has produced many of the current therapeutic options. The greatest challenge to designing a therapeutic inhibitor of SARS-CoV-2 is the shifting mutational landscape of the virus as it evolves. In this study, we focus on the spike protein as a target for potential inhibitors. We explore two methods of inhibiting spike function, allosteric inhibition and direct inhibition. In the study of allosteric inhibition, we screened two compound libraries against two allosteric sites. In the study of direct inhibition, several top-performing direct inhibitors of the wildtype spike were evaluated against five variants, B.1.1.7, B.1.351, P.1, B.1.617.2, and B.1.1.529. In summary, we identify four potential allosteric inhibitors that warrant further in-vitro study. We also find that the direct potential inhibitors of the wildtype spike had the most similar performance against the B.1.617.2 and B.1.1.7 variants

SPIDR: Small-Molecule Peptide-Influenced Drug Repurposing

Background: Conventional de novo drug design is costly and time consuming, making it accessible to only the best resourced research organizations. An emergent approach to new drug development is drug repurposing, in which compounds that have already gone through some level of clinical testing are examined for efficacy against diseases divergent than their original application. Repurposing of existing drugs circumvents the time and considerable cost of early stages of drug development, and can be accelerated by using software to screen existing chemical databases to identify suitable drug candidates. Results: Small-molecule Peptide-Influenced Drug Repurposing (SPIDR) was developed to identify small molecule drugs that target a specific receptor by exploring the conformational binding space of peptide ligands. SPIDR was tested using the potent and selective 16-amino acid peptide α-conotoxin MII ligand and the α3β2-nicotinic acetylcholine receptor (nAChR) isoform. SPIDR incorporates a genetic algorithm-based, heuristic search procedure, which was used to explore the ligand binding domain of the α3β2-nAChR isoform using a library consisting of 640,000 α-conotoxin MII peptide analogs. The peptides that exhibited the highest affinity for α3β2-nAChR were used as models for a small-molecule structure similarity search of the PubChem Compound database. SPIDR incorporates the SimSearcher utility, which generates shape distribution signatures of molecules and employs multi-level K-means clustering to insure fast database queries. SPIDR identified non-peptide drugs with estimated binding affinities nearly double that of the native α-conotoxin MII peptide. Conclusions: SPIDR has been generalized and integrated into DockoMatic v 2.1. This software contains an intuitive graphical interface for peptide mutant screening workflow and facilitates mapping, clustering, and searching of local molecular databases, making DockoMatic a valuable tool for researchers in drug design and repurposing

Flickr: A case study of Web2.0

The “photosharing” site Flickr is one of the most commonly cited examples used to define Web2.0. This paper explores where Flickr’s real novelty lies, examining its functionality and its place in the world of amateur photography. The paper draws on a wide range of sources including published interviews with its developers, user opinions expressed in forums, telephone interviews and content analysis of user profiles and activity. Flickr’s development path passes from an innovative social game to a relatively familiar model of a website, itself developed through intense user participation but later stabilising with the reassertion of a commercial relationship to the membership. The broader context of the impact of Flickr is examined by looking at the institutions of amateur photography and particularly the code of pictorialism promoted by the clubs and industry during the C20th. The nature of Flickr as a benign space is premised on the way the democratic potential of photography is controlled by such institutions. Several optimistic views of the impact of Flickr such as its facilitation of citizen journalism, “vernacular creativity” and in learning as an “affinity space” are evaluated. The limits of these claims are identified in the way that the system is designed to satisfy commercial purposes, continuing digital divides in access and the low interactivity and criticality on Flickr. Flickr is an interesting source of change, but can only to be understood in the perspective of long term development of the hobby and wider social processes

Specificity Determination by paralogous winged helix-turn-helix transcription factors

Transcription factors (TFs) localize to regulatory regions throughout the genome, where they exert physical or enzymatic control over the transcriptional machinery and regulate expression of target genes. Despite the substantial diversity of TFs found across all kingdoms of life, most belong to a relatively small number of structural families characterized by homologous DNA-binding domains (DBDs). In homologous DBDs, highly-conserved DNA-contacting residues define a characteristic ‘recognition potential’, or the limited sequence space containing high-affinity binding sites. Specificity-determining residues (SDRs) alter DNA binding preferences to further delineate this sequence space between homologous TFs, enabling functional divergence through the recognition of distinct genomic binding sites. This thesis explores the divergent DNA-binding preferences among dimeric, winged helix-turn-helix (wHTH) TFs belonging to the OmpR sub-family. As the terminal effectors of orthogonal two-component signaling pathways in Escherichia coli, OmpR paralogs bind distinct genomic sequences and regulate the expression of largely non-overlapping gene networks. Using high-throughput SELEX, I discover multiple sources of variation in DNA-binding, including the spacing and orientation of monomer sites as well as a novel binding ‘mode’ with unique half-site preferences (but retaining dimeric architecture). Surprisingly, given the diversity of residues observed occupying positions in contact with DNA, there are only minor quantitative differences in sequence-specificity between OmpR paralogs. Combining phylogenetic, structural, and biological information, I then define a comprehensive set of putative SDRs, which, although distributed broadly across the protein:DNA interface, preferentially localize to the major groove of the DNA helix. Direct specificity profiling of SDR variants reveals that individual SDRs impact local base preferences as well as global structural properties of the protein:DNA complex. This study demonstrates clearly that OmpR family TFs possess multiple ‘axes of divergence’, including base recognition, dimeric architecture, and structural attributes of the protein:DNA complex. It also provides evidence for a common structural ‘code’ for DNA-binding by OmpR homologues, and demonstrates that surprisingly modest residue changes can enable recognition of highly divergent sequence motifs. Importantly, well-characterized genomic binding sites for many of the TFs in this study diverge substantially from the presented de novo models, and it is unclear how mutations may affect binding in more complex environments. Further analysis using native sequences is required to build combined models of cis- and trans-evolution of two-component regulatory networks

Networks of Gratitude: Structures of Thanks and User Expectations in Workplace Appreciation Systems

Appreciation systems--platforms for users to exchange thanks and praise--are becoming common in the workplace, where employees share appreciation, managers are notified, and aggregate scores are sometimes made visible. Who do people thank on these systems, and what do they expect from each other and their managers? After introducing the design affordances of 13 appreciation systems, we discuss a system we call Gratia, in use at a large multinational company for over four years. Using logs of 422,000 appreciation messages and user surveys, we explore the social dynamics of use and ask if use of the system addresses the recognition problem. We find that while thanks is mostly exchanged among employees at the same level and different parts of the company, addressing the recognition problem, managers do not always act on that recognition in ways that employees expect.Comment: in Tenth International AAAI Conference on Web and Social Media, 201