Search Results - "Joe, Soobok"

Prediction model construction of mouse stem cell pluripotency using CpG and non-CpG DNA methylation markers by Joe, Soobok, Nam, Hojung

“…Genome-wide studies of DNA methylation across the epigenetic landscape provide insights into the heterogeneity of pluripotent embryonic stem cells (ESCs)…”
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Development of Tissue-Specific Age Predictors Using DNA Methylation Data by Choi, Heeyeon, Joe, Soobok, Nam, Hojung

“…DNA methylation patterns have been shown to change throughout the normal aging process. Several studies have found epigenetic aging markers using age…”
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Comparison of structural variant callers for massive whole-genome sequence data by Joe, Soobok, Park, Jong-Lyul, Kim, Jun, Kim, Sangok, Park, Ji-Hwan, Yeo, Min-Kyung, Lee, Dongyoon, Yang, Jin Ok, Kim, Seon-Young

“…Detecting structural variations (SVs) at the population level using next-generation sequencing (NGS) requires substantial computational resources and…”
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Comprehensive profiling of DNA methylation in Korean patients with colorectal cancer by Shim, Hyeran, Jang, Kiwon, Bang, Yeong Hak, Chu, Hoang Bao Khanh, Kang, Jisun, Lee, Jin-Young, Cho, Sheehyun, Lee, Hong Seok, Jeon, Jongbum, Hwang, Taeyeon, Joe, Soobok, Lim, Jinyeong, Choi, Ji-Hye, Joo, Eun Hye, Park, Kyunghee, Moon, Ji Hwan, Han, Kyung Yeon, Hong, Yourae, Lee, Woo Yong, Kim, Hee Cheol, Yun, Seong Hyeon, Cho, Yong Beom, Park, Yoon Ah, Huh, Jung Wook, Shin, Jung Kyong, Pyo, Dae Hee, Hong, Hyekyung, Lee, Hae-Ock, Park, Woong-Yang, Yang, Jin Ok, Kim, Young-Joon

“…Alterations in DNA methylation play an important pathophysiological role in the development and progression of colorectal cancer. We comprehensively profiled…”
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Prognostic factor analysis for breast cancer using gene expression profiles by Joe, Soobok, Nam, Hojung

“…The survival of patients with breast cancer is highly sporadic, from a few months to more than 15 years. In recent studies, the gene expression profiling of…”
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KTED: a comprehensive Web-Based database for transposable elements in the korean genome by Lee, Jin-Ok, Lee, Sejoon, Lee, Dongyoon, Hwang, Taeyeon, Joe, Soobok, Yang, Jin Ok, Jeong, Jibin, Ohn, Jung Hun, Kim, Jee Hyun

“…Abstract Summary Transposable Elements (TEs), commonly referred to as 'mobile elements,' constitute DNA segments capable of relocating within a genome…”
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Epigenetic insights into colorectal cancer: comprehensive genome-wide DNA methylation profiling of 294 patients in Korea by Joe, Soobok, Kim, Jinyong, Lee, Jin-Young, Jeon, Jongbum, Byeon, Iksu, Han, Sae-Won, Ryoo, Seung-Bum, Park, Kyu Joo, Song, Sang-Hyun, Cho, Sheehyun, Shim, Hyeran, Bao Khanh Chu, Hoang, Kang, Jisun, Lee, Hong Seok, Kim, DongWoo, Kim, Young-Joon, Kim, Tae-You, Kim, Seon-Young

“…DNA methylation regulates gene expression and contributes to tumorigenesis in the early stages of cancer. In colorectal cancer (CRC), CpG island methylator…”
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Exploring the DNA methylome of Korean patients with colorectal cancer consolidates the clinical implications of cancer-associated methylation markers by Lee, Sejoon, Lee, Kil-Yong, Park, Ji-Hwan, Kim, Duck-Woo, Oh, Heung-Kwon, Oh, Seong-Taek, Jeon, Jongbum, Lee, Dongyoon, Joe, Soobok, Chu, Hoang Bao Khanh, Kang, Jisun, Lee, Jin-Young, Cho, Sheehyun, Shim, Hyeran, Kim, Si-Cho, Lee, Hong Seok, Kim, Young-Joon, Yang, Jin Ok, Lee, Jaeim, Kang, Sung-Bum

“…Aberrant DNA methylation plays a critical role in the development and progression of colorectal cancer (CRC), which has high incidence and mortality rates in…”
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Deciphering the DNA methylation landscape of colorectal cancer in a Korean cohort by Lim, Seok-Byung, Joe, Soobok, Kim, Hyo-Ju, Lee, Jong Lyul, Park, In Ja, Yoon, Yong Sik, Kim, Chan Wook, Kim, Jong-Hwan, Kim, Sangok, Lee, Jin-Young, Shim, Hyeran, Bao Khanh Chu, Hoang, Cho, Sheehyun, Kang, Jisun, Kim, Si-Cho, Lee, Hong Seok, Kim, Young-Joon, Kim, Seon-Young, Yu, Chang Sik

“…Aberrant DNA methylation plays a pivotal role in the onset and progression of colorectal cancer (CRC), a disease with high incidence and mortality rates in…”
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Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research by Golob, Jonathan L, Oskotsky, Tomiko T, Tang, Alice S, Roldan, Alennie, Chung, Verena, Ha, Connie W Y, Wong, Ronald J, Flynn, Kaitlin J, Parraga-Leo, Antonio, Wibrand, Camilla, Minot, Samuel S, Oskotsky, Boris, Andreoletti, Gaia, Kosti, Idit, Bletz, Julie, Nelson, Amber, Gao, Jifan, Wei, Zhoujingpeng, Chen, Guanhua, Tang, Zheng-Zheng, Novielli, Pierfrancesco, Romano, Donato, Pantaleo, Ester, Amoroso, Nicola, Monaco, Alfonso, Vacca, Mirco, De Angelis, Maria, Bellotti, Roberto, Tangaro, Sabina, Kuntzleman, Abigail, Bigcraft, Isaac, Techtmann, Stephen, Bae, Daehun, Kim, Eunyoung, Jeon, Jongbum, Joe, Soobok, Theis, Kevin R, Ng, Sherrianne, Lee, Yun S, Diaz-Gimeno, Patricia, Bennett, Phillip R, MacIntyre, David A, Stolovitzky, Gustavo, Lynch, Susan V, Albrecht, Jake, Gomez-Lopez, Nardhy, Romero, Roberto, Stevenson, David K, Aghaeepour, Nima, Tarca, Adi L, Costello, James C, Sirota, Marina

“…Every year, 11% of infants are born preterm with significant health consequences, with the vaginal microbiome a risk factor for preterm birth. We crowdsource…”
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