日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Insights on improving accessibility and usability of functional data to unlock their potential for variant interpretation

深入探讨如何提高功能数据的可访问性和可用性,从而释放其在变异解读方面的潜力

Park, Min Seon; Kumar, Runjun D; Ovadiuc, Cristian; Folta, Andrew; McEwen, Abbye E; Snyder, Ashley; Villani, Rehan M; Spurdle, Amanda B; Fowler, Douglas M; Rubin, Alan F; Shirts, Brian H; Starita, Lea M; Stergachis, Andrew B

Heterozygous CELF4 variants in the N-term region crucial for the RNA-binding activity lead to neurodevelopmental disorder and obesity

CELF4基因N端区域的杂合变异(该区域对RNA结合活性至关重要)会导致神经发育障碍和肥胖。

Bruel, Ange-Line; Vulto-vanSilfhout, Anneke T; Bilan, Frédéric; Le Guyader, Gwenaël; Gilbert-Dussardier, Brigitte; Le Guillou, Xavier; Rondeau, Sophie; Rio, Marlène; Lee, Kristen N; Beil, Adelyn; Suri, Mohnish; Guerin, François; Ruault, Valentin; Goldenberg, Alice; Lecoquierre, François; Bertsch, Nicole; Anderson, Rhonda; Yang, Xiao-Ru; Inness, Micheil; Rikeros-Orozco, Emi; Palomares-Bralo, Maria; Hayek, Jennifer Cassady; Cech, Jennifer; Jhuraney, Ankita; Kumar, Runjun D; Mercimek-Andrews, Saadet; Ambrose, Anastasia; Wakeling, Erin N; Wentzensen, Ingrid M; Torti, Erin; Gooch, Catherine; Faivre, Laurence; Philippe, Christophe; Duffourd, Yannis; Vitobello, Antonio; Thauvin-Robinet, Christel

Long-read transcriptome analysis using IsoRanker for identifying pathogenic variants in Mendelian conditions

利用 IsoRanker 进行长读长转录组分析,以识别孟德尔遗传病中的致病变异。

Cheng, Yong-Han Hank; Sedeño-Cortés, Adriana E; Ranchalis, Jane E; Munson, Katherine M; Vollger, Mitchell R; Balton, Elsa; Genetti, Casie A; Wojcik, Monica H; Beggs, Alan H; Bamshad, Michael J; Wei, Chia-Lin; Dipple, Katrina M; Kumar, Runjun D; Blue, Elizabeth E; Jarvik, Gail; Chong, Jessica X; Witten, Daniela M; O'Donnell-Luria, Anne; Stergachis, Andrew B

Insights on improving accessibility and usability of functional data to unlock its potential for variant interpretation

深入探讨如何提高功能数据的可访问性和可用性,从而释放其在变异解读方面的潜力

Park, Min Seon; Kumar, Runjun D; Ovadiuc, Cristian; Folta, Andrew; McEwen, Abbye E; Snyder, Ashley; Fowler, Douglas M; Rubin, Alan F; Shirts, Brian H; Starita, Lea M; Stergachis, Andrew B

Analysis and Interpretation of Somatic NMD-Escaping Variants in Oncogenes and Dual-Function Genes across Adult and Pediatric Cancer Cohorts

对成人和儿童癌症队列中癌基因和双功能基因中体细胞NMD逃逸变异的分析和解释

Eldomery, Mohammad K; Dieseldorff Jones, Karissa M; Namwanje, Maria; Kumar, Runjun D; Li, Jiaming; Wilkinson, Mark R; Wang, Lu; Klco, Jeffery M; Tang, Li; Neary, Jennifer L; Plon, Sharon E; Blackburn, Patrick R

Clinical exome sequencing uncovers a high frequency of Mendelian disorders in infants with stroke: A retrospective analysis

临床外显子组测序揭示婴儿卒中患者中孟德尔遗传病的高发率:一项回顾性分析

Kumar, Runjun D; Meng, Linyan; Liu, Pengfei; Miyake, Christina Y; Worley, Kim C; Bi, Weimin; Lalani, Seema R

A deep intronic variant is a common cause of OTC deficiency in individuals with previously negative genetic testing

深内含子变异是既往基因检测结果为阴性的个体中鸟氨酸氨甲酰转移酶(OTC)缺乏症的常见原因。

Kumar, Runjun D; Burrage, Lindsay C; Bartos, Jan; Ali, Saima; Schmitt, Eric; Nagamani, Sandesh C S; LeMons, Cynthia

A TMPRSS2-ERG gene signature predicts prognosis of patients with prostate adenocarcinoma

TMPRSS2-ERG基因特征可预测前列腺腺癌患者的预后

Zhou, Emily; Zhang, Baoyi; Zhu, Kenneth; Schaafsma, Evelien; Kumar, Runjun D; Cheng, Chao

The prognostic effects of somatic mutations in ER-positive breast cancer

ER阳性乳腺癌体细胞突变的预后效应

Griffith, Obi L; Spies, Nicholas C; Anurag, Meenakshi; Griffith, Malachi; Luo, Jingqin; Tu, Dongsheng; Yeo, Belinda; Kunisaki, Jason; Miller, Christopher A; Krysiak, Kilannin; Hundal, Jasreet; Ainscough, Benjamin J; Skidmore, Zachary L; Campbell, Katie; Kumar, Runjun; Fronick, Catrina; Cook, Lisa; Snider, Jacqueline E; Davies, Sherri; Kavuri, Shyam M; Chang, Eric C; Magrini, Vincent; Larson, David E; Fulton, Robert S; Liu, Shuzhen; Leung, Samuel; Voduc, David; Bose, Ron; Dowsett, Mitch; Wilson, Richard K; Nielsen, Torsten O; Mardis, Elaine R; Ellis, Matthew J

Statistically identifying tumor suppressors and oncogenes from pan-cancer genome-sequencing data

利用泛癌基因组测序数据,通过统计学方法识别肿瘤抑制基因和癌基因

Kumar, Runjun D; Searleman, Adam C; Swamidass, S Joshua; Griffith, Obi L; Bose, Ron