A Syllable-based Technique for Word Embeddings of Korean Words

Word embedding has become a fundamental component to many NLP tasks such as named entity recognition and machine translation. However, popular models that learn such embeddings are unaware of the morphology of words, so it is not directly applicable to highly agglutinative languages such as Korean. We propose a syllable-based learning model for Korean using a convolutional neural network, in which word representation is composed of trained syllable vectors. Our model successfully produces morphologically meaningful representation of Korean words compared to the original Skip-gram embeddings. The results also show that it is quite robust to the Out-of-Vocabulary problem.Comment: 5 pages, 3 figures, 1 table. Accepted for EMNLP 2017 Workshop - The 1st Workshop on Subword and Character level models in NLP (SCLeM

The Effect Of Internal Capital Market Of Korean Large Business Groups On Investment Efficiency

This study examines whether the effect of funding through internal capital markets on investment efficiency is differentiated by the incentives of controlling shareholders as measured by the divergence between cash flow rights and voting rights of controlling shareholders (hereafter, wedge). To empirically analyze hypotheses of this study, 1,189 firm-year observations were collected from Korean firms listed on the Korea Composite Stock Price Index (KOSPI) belonging to a large business group designated by the Korea Fair Trade Commission over the period from 2005 to 2012. The results of the analysis are as follows. First, we find that the magnitude of internal funding, as measured by total payables to the related parties, is positively (+) associated with investment inefficiency. Second, the interaction variables of total payables to the related parties and the wedge have a significant positive (+) effect on investment inefficiency. In other words, the deterioration of investment efficiency due to the increase in total payables to the related parties was mainly caused by firms with a big wedge. This result suggests that the effect of internal capital markets on investment efficiency of large business groups may be differentiated by the wedge that is proxy of the controlling shareholder’s incentive. This study provides additional evidence on previous studies on the investment efficiency of large business groups by considering both the internal capital market and incentives for funding using the internal capital market, which are important factors affecting the investment of large corporate groups. Also, the results of this study are expected to provide implications for the regulatory policy of large business groups which have recently become an issue in Korea

Studying cancer immunotherapy using patient-derived xenografts (PDXs) in humanized mice.

Cancer immunotherapy is a promising way to eliminate tumor cells by using the patient\u27s own immune system. Selecting the appropriate animal models to develop or validate preclinical immunotherapeutic trials is now an important aspect of many cancer research programs. Here we discuss the advantages and limitations of using genetically engineered immunodeficient mouse models, patient-derived xenografts (PDXs), and humanized mouse models for developing and testing immunotherapeutic strategies

iCSDB: an integrated database of CRISPR screens.

High-throughput screening based on CRISPR-Cas9 libraries has become an attractive and powerful technique to identify target genes for functional studies. However, accessibility of public data is limited due to the lack of user-friendly utilities and up-to-date resources covering experiments from third parties. Here, we describe iCSDB, an integrated database of CRISPR screening experiments using human cell lines. We compiled two major sources of CRISPR-Cas9 screening: the DepMap portal and BioGRID ORCS. DepMap portal itself is an integrated database that includes three large-scale projects of CRISPR screening. We additionally aggregated CRISPR screens from BioGRID ORCS that is a collection of screening results from PubMed articles. Currently, iCSDB contains 1375 genome-wide screens across 976 human cell lines, covering 28 tissues and 70 cancer types. Importantly, the batch effects from different CRISPR libraries were removed and the screening scores were converted into a single metric to estimate the knockout efficiency. Clinical and molecular information were also integrated to help users to select cell lines of interest readily. Furthermore, we have implemented various interactive tools and viewers to facilitate users to choose, examine and compare the screen results both at the gene and guide RNA levels. iCSDB is available at https://www.kobic.re.kr/icsdb/

Genome-scale CRISPR screening identifies cell cycle and protein ubiquitination processes as druggable targets for erlotinib-resistant lung cancer.

Erlotinib is highly effective in lung cancer patients with epidermal growth factor receptor (EGFR) mutations. However, despite initial favorable responses, most patients rapidly develop resistance to erlotinib soon after the initial treatment. This study aims to identify new genes and pathways associated with erlotinib resistance mechanisms in order to develop novel therapeutic strategies. Here, we induced knockout (KO) mutations in erlotinib-resistant human lung cancer cells (NCI-H820) using a genome-scale CRISPR-Cas9 sgRNA library to screen for genes involved in erlotinib susceptibility. The spectrum of sgRNAs incorporated among erlotinib-treated cells was substantially different to that of the untreated cells. Gene set analyses showed a significant depletion of \u27cell cycle process\u27 and \u27protein ubiquitination pathway\u27 genes among erlotinib-treated cells. Chemical inhibitors targeting genes in these two pathways, such as nutlin-3 and carfilzomib, increased cancer cell death when combined with erlotinib in both in vitro cell line and in vivo patient-derived xenograft experiments. Therefore, we propose that targeting cell cycle processes or protein ubiquitination pathways are promising treatment strategies for overcoming resistance to EGFR inhibitors in lung cancer