• Genomics & Informatics
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• v.15 no.1
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• pp.51-53
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• 2017

High-throughput transcriptome sequencing, also known as RNA sequencing (RNA-Seq), is a standard technology for measuring gene expression with unprecedented accuracy. Numerous bioconductor packages have been developed for the statistical analysis of RNA-Seq data. However, these tools focus on specific aspects of the data analysis pipeline, and are difficult to appropriately integrate with one another due to their disparate data structures and processing methods. They also lack visualization methods to confirm the integrity of the data and the process. In this paper, we propose an R-based RNA-Seq analysis pipeline called TRAPR, an integrated tool that facilitates the statistical analysis and visualization of RNA-Seq expression data. TRAPR provides various functions for data management, the filtering of low-quality data, normalization, transformation, statistical analysis, data visualization, and result visualization that allow researchers to build customized analysis pipelines.

• Genomics & Informatics
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• v.3 no.1
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• pp.39-42
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• 2005

DNA microarray is a high-throughput biomedical technology that monitors gene expression for thousands of genes in parallel. The abundance and complexity of the gene expression data have given rise to a requirement for their systematic management and analysis to support many laboratories performing microarray research. On these demands, we developed Xperanto for integrated data management and analysis using user-friendly web-based interface. Xperanto provides an integrated environment for management and analysis by linking the computational tools and rich sources of biological annotation. With the growing needs of data sharing, it is designed to be compliant to MGED (Microarray Gene Expression Data) standards for microarray data annotation and exchange. Xperanto enables a fast and efficient management of vast amounts of data, and serves as a communication channel among multiple researchers within an emerging interdisciplinary field.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.2
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• pp.56-62
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• 2010

The purpose of this study was to compare the difference of driving pattern between male and female drivers for a straight driving and unexpected situation using driving simulator and motion data. The participants included total 60 university students; 30 males aged 24.3$\pm$1.4 years and 30 females aged 23.2$\pm$1.9 years with 1~3 years of driving experience. The driving task required participants to keep the constant distance (20m, 25m or 30m) with preceding vehicle running at 55~65km/hr speed using driving simulator which was programed unexpected situation for two minutes. Simulator and motion data were acquired. The acquired data was divided in straight driving block for 40 second and unexpected situation block for 2 second. The coefficient of variation (CV) of lane keeping and jerk-cost (JC) function were analyzed for straight driving and unexpected situation blocks. The results show that CV was smaller in males than females for both straight and unexpected situation blocks (p < .05). JC was smaller in females than males for both straight and unexpected situation blocks. As the distance of vehicles become longer, JC was smaller for both male and female (p < .05).

• Proceedings of the KOSOMBE Conference
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• v.1994 no.05
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• pp.53-56
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• 1994

We have developed biological signal measurement modules and data acquisition and control card for a biological signal measurement, archiving, and communication system (SiMACS). Biological signals included in this system are ECG, EEG, EMG, invasive blood pressure, respiration, and temperature. Parameters of each module can be controlled by PC-base IDPU (intelligent data processing unit) through a data acquisition and control card. The data acquisition and control card can collect up to 16 channels of biological signals with sampling rate of $50\;{\sim}\;2,000Hz$ and 12-bit resolution. All measurement moduls and data acquisition functions are controlled by microcontroller which receives commands from PC. All data transfers among PC, microcontroller, and ADC are done through a shared RAM access by polling method for real rime operation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1830-1840
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• 2011

CDISC (Clinical Data Interchanging Standards Consortium) standards are to support the acquisition, exchange, submission and archival of clinical trial and research data. SDTM (Study Data Tabulation Model) for Case Report Forms (CRFs) was recommended for U.S. Food and Drug Administration (FDA) regulatory submissions since 2004. Although the SDTM Implementation Guide gives a standardized and predefined collection of submission metadata 'domains' containing extensive variable collections, transforming CRFs to SDTM files for FDA submission is still a very hard and time-consuming task. For addressing this issue, we developed metadata based SDTM mapping rules. Using these mapping rules, we also developed a semi-automatic tool, named CDISC Transformer, for transforming clinical trial data to CDISC standard compliant data. The performance of CDISC Transformer with or without MDR support was evaluated using CDISC blank CRF as the 'gold standard'. Both MDR and user inquiry-supported transformation substantially improved the accuracy of our transformation rules. CDISC Transformer will greatly reduce the workloads and enhance standardized data entry and integration for clinical trial and research in various healthcare domains.

• Journal of Computing Science and Engineering
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• v.10 no.1
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• pp.21-31
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• 2016

With the application and development of biomedical techniques such as next-generation sequencing, mass spectrometry, and medical imaging, the amount of biomedical data have been growing explosively. In terms of processing such data, we face the problems surrounding big data, highly intensive computation, and high dimensionality data. Fortunately, cloud computing represents significant advantages of resource allocation, data storage, computation, and sharing and offers a solution to solve big data problems of biomedical research. In order to improve the efficiency of resource management in cloud computing, this paper proposes a clustering method and adopts Radial Basis Function in order to compress comprehensive data sets found in biology and medicine in high quality, and stores these data with resource management in cloud computing. Experiments have validated that with such a data-compression-based resource management in cloud computing, one can store large data sets from biology and medicine in fewer capacities. Furthermore, with reverse operation of the Radial Basis Function, these compressed data can be reconstructed with high accuracy.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.29-34
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• 2005

DNA microarray becomes a major tool for the investigation of global gene expression in all aspects of cancer and biomedical research. DNA microarray experiment generates enormous amounts of data and they are meaningful only in the context of a detailed description of microarrays, biomaterials, and conditions under which they were generated. MicroArray Gene Expression Data (MGED) society has established microarray standard for structured management of these diverse and large amount data. MGED MAGE-OM (MicroArray Gene Expression Object Model) is an object oriented data model, which attempts to define standard objects for gene expression. To assess the relevance of DNA microarray analysis of cancer research it is required to combine clinical and genomics data. MAGE-OM, however, does not have an appropriate structure to describe clinical information of cancer. For systematic integration of gene expression and clinical data, we create a new model, Cancer Genomics Object Model.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.153-154
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• 1998

As the fundamental study to set up the algorithm of the X-ray dosimeter, we obtained the data using the designed X-ray input circuit and the semiconductor sensor. We measured the data of the ten time in the various kVp, mA and sec and then the obtained each data is averaged. After the data obtained under the circumstances of total 600, these data saved the database. We developed the algorithm of the X-ray dosimeter using the saved data. Later the result of this study is so important to design X-ray dosimeter.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.304-306
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• 1996

Endoscopy has become a crucial diagnostic and theraputic procedure in clinical areas. Over the past three years, we have developed a computerized system to record and store clinical data pertaining to endoscopic surgery of laparascopic cholesystectomy, peviscopic endometriosis, and surgical arthroscopy. In this study, we are developed computer system, which is composed of frame grabber, sound board, VCR control board, LAN card and EDMS(endoscopic data management software). Also, computer system has controled over peripheral instruments as a color video printer, video cassette recorder, and endoscopic input/output signals(image and doctor's speech). Also, we are developed one body system of camels control unit including an endoscopic miniature camera and light source. Our system offer unsurpassed image quality in terms of resolution and color fidelity. Digital endoscopic data management system is based on open architecture and a set of widely available industry standards, namely: windows 3.1 as a operating system, TCP/IP as a network protocol and a time sequence based database that handles both an image and drctor's speech synchronized with endoscopic image.

• Journal of Biomedical Engineering Research
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• v.30 no.3
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• pp.185-190
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• 2009

Biomedical mobile devices for ubiquitous healthcare consist of biomedical sensors and communication terminal. They have two types of configuration. One is the sensor-network type device using wired or wireless communication with intelligent sensors to acquire biomedical data. The other is the sensor embedded type device, where the data can be acquired directly by itself. There are many examples of sensor network type, such as, fall detection sensor, blood glucose sensor, and ECG sensors networked with commercial PDA phone and commercial phone terminal for ubiquitous healthcare. On the other hand, sensor embedded type mounts blood glucose sensor, accelerometer, and etc. on commercial phone. However, to enable true ubiquitous healthcare, motion sensing is essential, because users go around anywhere and their signals should be measured and monitored, when they are affected by the motion. Therefore, in this paper, two biomedical mobile devices with motion monitoring function were addressed. One is sensor-network type with motion monitoring function, which uses Zigbee communication to measure the ECG, PPG and acceleration. The other is sensor-embedded type with motion monitoring function, which also can measure the data and uses the built-in cellular phone network modem for remote connection. These devices are expected to be useful for ubiquitous healthcare in coming aged society in Korea.