Hyojin Kim

TRRUST: A reference database of human transcriptional regulatory interactions

The reconstruction of transcriptional regulatory networks (TRNs) is a long-standing challenge in human genetics. Numerous computational methods have been developed to infer regulatory interactions between human transcriptional factors (TFs) and target genes from high-throughput data, and their performance evaluation requires gold-standard interactions. Here we present a database of literature-curated human TF-target interactions, TRRUST (transcriptional regulatory relationships unravelled by sentence-based text-mining, http://www.grnpedia.org/trrust), which currently contains 8,015 interactions between 748 TF genes and 1,975 non-TF genes. A sentence-based text-mining approach was employed for efficient manual curation of regulatory interactions from approximately 20 million Medline abstracts. To the best of our knowledge, TRRUST is the largest publicly available database of literature-curated human TF-target interactions to date. TRRUST also has several useful features: i) information about the mode-of-regulation; ii) tests for target modularity of a query TF; iii) tests for TF cooperativity of a query target; iv) inferences about cooperating TFs of a query TF; and v) prioritizing associated pathways and diseases with a query TF. We observed high enrichment of TF-target pairs in TRRUST for top-scored interactions inferred from high-throughput data, which suggests that TRRUST provides a reliable benchmark for the computational reconstruction of human TRNs.

AraNet v2: an improved database of co-functional gene networks for the study of Arabidopsis thaliana and 27 other nonmodel plant species

Arabidopsis thaliana is a reference plant that has been studied intensively for several decades. Recent advances in high-throughput experimental technology have enabled the generation of an unprecedented amount of data from A. thaliana, which has facilitated data-driven approaches to unravel the genetic organization of plant phenotypes. We previously published a description of a genome-scale functional gene network for A. thaliana, AraNet, which was constructed by integrating multiple co-functional gene networks inferred from diverse data types, and we demonstrated the predictive power of this network for complex phenotypes. More recently, we have observed significant growth in the availability of omics data for A. thaliana as well as improvements in data analysis methods that we anticipate will further enhance the integrated database of co-functional networks. Here, we present an updated co-functional gene network for A. thaliana, AraNet v2 (available at http://www.inetbio.org/aranet), which covers approximately 84% of the coding genome. We demonstrate significant improvements in both genome coverage and accuracy. To enhance the usability of the network, we implemented an AraNet v2 web server, which generates functional predictions for A. thaliana and 27 nonmodel plant species using an orthology-based projection of nonmodel plant genes on the A. thaliana gene network.

YeastNet v3: a public database of data-specific and integrated functional gene networks for Saccharomyces cerevisiae

Saccharomyces cerevisiae, i.e. baker’s yeast, is a widely studied model organism in eukaryote genetics because of its simple protocols for genetic manipulation and phenotype profiling. The high abundance of publicly available data that has been generated through diverse ‘omics’ approaches has led to the use of yeast for many systems biology studies, including large-scale gene network modeling to better understand the molecular basis of the cellular phenotype. We have previously developed a genome-scale gene network for yeast, YeastNet v2, which has been used for various genetics and systems biology studies. Here, we present an updated version, YeastNet v3 (available at http://www.inetbio.org/yeastnet/), that significantly improves the prediction of gene–phenotype associations. The extended genome in YeastNet v3 covers up to 5818 genes (∼99% of the coding genome) wired by 362 512 functional links. YeastNet v3 provides a new web interface to run the tools for network-guided hypothesis generations. YeastNet v3 also provides edge information for all data-specific networks (∼2 million functional links) as well as the integrated networks. Therefore, users can construct alternative versions of the integrated network by applying their own data integration algorithm to the same data-specific links.

The electronic structure of C60/ZnPc interface for organic photovoltaic device with blended layer architecture

The interfacial electronic structures of fullerene (C60)/zinc-phthalocyanine (ZnPc) and C60/ZnPc:C60 (50 wtu2009%) containing a blended layer were investigated by in situ ultraviolet photoelectron spectroscopy (UPS), in an attempt to understand the role of the blended layer in improving the performance of organic photovoltaic devices that contain such layers. From the UPS spectra, the band bending found to be 0.30 eV in the ZnPc layer and 0.43 eV in the C60 layer at the C60/ZnPc interface. On the other hand, the band bending was 0.25 eV in both of the organic layers at the ZnPc:C60/ZnPc interface and no significant band bending in the C60 layer at the C60/ZnPc:C60 interface was found. The observed interface dipole was 0.06 eV at the C60/ZnPc interface and 0.26 eV at the ZnPc:C60/ZnPc interface. The offset between the highest unoccupied molecular orbital of ZnPc and the lowest occupied molecular orbital of C60 was 0.75 eV at C60/ZnPc and was 1.04 eV at the ZnPc:C60/ZnPc interface. The increased offset can be a...

Novel defense mechanism against data flooding attacks in wireless ad hoc networks

Mobile users like to use their own consumer electronic devices anywhere and at anytime to access multimedia data. Hence, we expect that wireless ad hoc networks will be widely used in the near future since these networks form the topology with low cost on the fly. However, consumer electronic devices generally operate on limited battery power and therefore are vulnerable to security threats like data flooding attacks. The data flooding attack causes Denial of Service (DoS) attacks by flooding many data packets. However, there are a few existing defense systems against data flooding attacks. Moreover, the existing schemes may not guarantee the Quality of Service (QoS) of burst traffic since multimedia data are usually burst. Therefore, we propose a novel defense mechanism against data flooding attacks with the aim of enhancing the throughput. The simulation results show that the proposed scheme enhances the throughput of burst traffic.

WormNet v3: a network-assisted hypothesis-generating server for Caenorhabditis elegans

High-throughput experimental technologies gradually shift the paradigm of biological research from hypothesis-validation toward hypothesis-generation science. Translating diverse types of large-scale experimental data into testable hypotheses, however, remains a daunting task. We previously demonstrated that heterogeneous genomics data can be integrated into a single genome-scale gene network with high prediction power for ribonucleic acid interference (RNAi) phenotypes in Caenorhabditis elegans, a popular metazoan model in the study of developmental biology, neurobiology and genetics. Here, we present WormNet version 3 (v3), which is a new network-assisted hypothesis-generating server for C. elegans. WormNet v3 includes major updates to the base gene network, which substantially improved predictions of RNAi phenotypes. The server generates various gene network-based hypotheses using three complementary network methods: (i) a phenotype-centric approach to ‘find new members for a pathway’; (ii) a gene-centric approach to ‘infer functions from network neighbors’ and (iii) a context-centric approach to ‘find context-associated hub genes’, which is a new method to identify key genes that mediate physiology within a specific context. For example, we demonstrated that the context-centric approach can be used to identify potential molecular targets of toxic chemicals. WormNet v3 is freely accessible at http://www.inetbio.org/wormnet.

Network-assisted crop systems genetics: network inference and integrative analysis

Although next-generation sequencing (NGS) technology has enabled the decoding of many crop species genomes, most of the underlying genetic components for economically important crop traits remain to be determined. Network approaches have proven useful for the study of the reference plant, Arabidopsis thaliana, and the success of network-based crop genetics will also require the availability of a genome-scale functional networks for crop species. In this review, we discuss how to construct functional networks and elucidate the holistic view of a crop system. The crop gene network then can be used for gene prioritization and the analysis of resequencing-based genome-wide association study (GWAS) data, the amount of which will rapidly grow in the field of crop science in the coming years.

TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions

Abstract Transcription factors (TFs) are major trans-acting factors in transcriptional regulation. Therefore, elucidating TF–target interactions is a key step toward understanding the regulatory circuitry underlying complex traits such as human diseases. We previously published a reference TF–target interaction database for humans—TRRUST (Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining)—which was constructed using sentence-based text mining, followed by manual curation. Here, we present TRRUST v2 (www.grnpedia.org/trrust) with a significant improvement from the previous version, including a significantly increased size of the database consisting of 8444 regulatory interactions for 800 TFs in humans. More importantly, TRRUST v2 also contains a database for TF–target interactions in mice, including 6552 TF–target interactions for 828 mouse TFs. TRRUST v2 is also substantially more comprehensive and less biased than other TF–target interaction databases. We also improved the web interface, which now enables prioritization of key TFs for a physiological condition depicted by a set of user-input transcriptional responsive genes. With the significant expansion in the database size and inclusion of the new web tool for TF prioritization, we believe that TRRUST v2 will be a versatile database for the study of the transcriptional regulation involved in human diseases.

Handling Malicious Flooding Attacks through Enhancement of Packet Processing Technique in Mobile Ad Hoc Networks

Abstract —Mobile ad hoc networks are expected to be widely used in the near future. However, they are susceptible to various security threats because of their inherent characteristics. Malicious flooding attacks are one of the fatal attacks on mobile ad hoc networks. These attacks can severely clog an entire network, as a result of clogging the victim node. If collaborative multiple attacks are conducted, it becomes more difficult to prevent. To defend against these attacks, we propose a novel defense mechanism in mobile ad hoc networks. The proposed scheme enhances the amount of legitimate packet processing at each node. The simulation results show that the proposed scheme also improves the end-to-end packet delivery ratio. Keywords —Collaborative Attack, Malicious Flooding Attack, Wireless Ad Hoc Network 1. I NTRODUCTION As many users like to use mobile equipment such as cell phones, smart phones, laptops etc. mobile ad hoc networks are expected to be widely used in the near future. Today’s mobile nodes have a broad range of applications. With the introduction of smart phones into the market, there is an immense need for privatization and security. Today’s mobile nodes do not have many restrictions in terms of processor speed etc. One main problem existing in mobile nodes in use these days is their battery life due to the immense energy that they de-pend upon. But, this is not the problem we will be discussing in the following paper. In the pre-sent research we assume that this energy is available in sufficient quantities for the mobile nodes to be able to function and process data. As the technology involving mobile nodes is developing at a fast pace, we expect that mobile ad hoc networks, which use mobile nodes as communication entities, will be widely used in the future. In mobile ad hoc networks, mobile nodes communicate with other nodes helped by neighboring nodes rather than base stations in a multi-hop fashion [1]. Hence, mobile ad hoc networks do not require any additional costs, such as costs for installing base stations, and are formed on-the-fly. However, all signals go through bandwidth-constrained wireless links [1]. Moreover, mobile nodes used in mobile ad hoc networks are compact and portable, so they have limited resources

SNS users' para-social relationships with celebrities: social media effects on purchase intentions

In this study, the authors investigate factors that influence para-social relationships between social network service (SNS) users and celebrities and the effects on users purchase intentions. The study shows that SNS use and para-social relationships with celebrities are positively related. User/celebrity para-social relationships and celebrity reputation also show positive relationships with purchase intentions. Gender differences affect relationships between celebrity reputation, para-social relationships and purchase intentions. The results imply that new media, particularly SNS, encourages para-social relationships, and that para-social relationships and celebrity reputations persuade SNS users to make purchase decisions. The study shows that new media stimulates consumer desires, and the new SNS environment gives celebrities more power to affect purchase decisions.