Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Simon M Lin"'
Publikováno v:
Cancer Informatics, Vol 1, Pp 32-40 (2005)
Abstract: The use of MALDI-TOF mass spectrometry as a means of analyzing the proteome has been evaluated extensively in recent years. One of the limitations of this technique that has impeded the development of robust data analysis algorithms is the
Externí odkaz:
https://doaj.org/article/194569de143942738638799104a1ad4b
Publikováno v:
PLoS ONE, Vol 7, Iss 12, p e49686 (2012)
Identification of gene-disease association is crucial to understanding disease mechanism. A rapid increase in biomedical literatures, led by advances of genome-scale technologies, poses challenge for manually-curated-based annotation databases to cha
Externí odkaz:
https://doaj.org/article/c3c974a9349c4eec962f4bc8be06aaf6
Publikováno v:
PLoS ONE, Vol 7, Iss 10, p e46450 (2012)
The advent of next-generation sequencing technologies has greatly promoted the field of metagenomics which studies genetic material recovered directly from an environment. Characterization of genomic composition of a metagenomic sample is essential f
Externí odkaz:
https://doaj.org/article/33bbf61e68774a10af1f7a43fae030bd
Autor:
Antonia Navarro, Ping Yin, Diana Monsivais, Simon M Lin, Pan Du, Jian-Jun Wei, Serdar E Bulun
Publikováno v:
PLoS ONE, Vol 7, Iss 3, p e33284 (2012)
Uterine leiomyomas, or fibroids, represent the most common benign tumor of the female reproductive tract. Fibroids become symptomatic in 30% of all women and up to 70% of African American women of reproductive age. Epigenetic dysregulation of individ
Externí odkaz:
https://doaj.org/article/d0b0f6fe426740d7901047323c453fe4
Autor:
Huixiao Hong, Lei Xu, Jie Liu, Wendell D Jones, Zhenqiang Su, Baitang Ning, Roger Perkins, Weigong Ge, Kelci Miclaus, Li Zhang, Kyunghee Park, Bridgett Green, Tao Han, Hong Fang, Christophe G Lambert, Silvia C Vega, Simon M Lin, Nadereh Jafari, Wendy Czika, Russell D Wolfinger, Federico Goodsaid, Weida Tong, Leming Shi
Publikováno v:
PLoS ONE, Vol 7, Iss 9, p e44483 (2012)
During the last several years, high-density genotyping SNP arrays have facilitated genome-wide association studies (GWAS) that successfully identified common genetic variants associated with a variety of phenotypes. However, each of the identified ge
Externí odkaz:
https://doaj.org/article/f7b0abb5339e435fa63dd591f9847118
Publikováno v:
PLoS Computational Biology, Vol 7, Iss 11, p e1002259 (2011)
Externí odkaz:
https://doaj.org/article/71c6533a5d10430ab17f97e2fddeb8b8
Autor:
Haixi Miao, Lin Chen, Sean M Riordan, Wenjun Li, Santiago Juarez, Andrea M Crabb, Thomas J Lukas, Pan Du, Simon M Lin, Alexandria Wise, Olga A Agapova, Ping Yang, Charles C Gu, M Rosario Hernandez
Publikováno v:
PLoS ONE, Vol 3, Iss 8, p e2847 (2008)
To determine whether optic nerve head (ONH) astrocytes, a key cellular component of glaucomatous neuropathy, exhibit differential gene expression in primary cultures of astrocytes from normal African American (AA) donors compared to astrocytes from n
Externí odkaz:
https://doaj.org/article/462ab6ea1c5a4cd5815a8c6bd7eb7780
Publikováno v:
Cancer Informatics, Vol 1 (2005)
The use of MALDI-TOF mass spectrometry as a means of analyzing the proteome has been evaluated extensively in recent years. One of the limitations of this technique that has impeded the development of robust data analysis algorithms is the variabilit
Externí odkaz:
https://doaj.org/article/318d1944ec564d348d8c04fb9673bb83
Autor:
Rajeswari Swaminathan, Yungui Huang, Soheil Moosavinasab, Ronald Buckley, Christopher W. Bartlett, Simon M. Lin
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 14, Iss C, Pp 8-15 (2016)
The constant improvement and falling prices of whole human genome Next Generation Sequencing (NGS) has resulted in rapid adoption of genomic information at both clinics and research institutions. Considered together, the complexity of genomics data,
Externí odkaz:
https://doaj.org/article/1fab1b21556543579b45194bbe94a6a3
Autor:
En-Ju D, Lin, Jennifer L, Hefner, Xianlong, Zeng, Soheil, Moosavinasab, Thomas, Huber, Jennifer, Klima, Chang, Liu, Simon M, Lin
Publikováno v:
The American journal of managed care. 25(10)
Current models for patient risk prediction rely on practitioner expertise and domain knowledge. This study presents a deep learning model-a type of machine learning that does not require human inputs-to analyze complex clinical and financial data for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::61d4b0265cb9fb272e0a4a7a9d069844
https://pubmed.ncbi.nlm.nih.gov/31622071
https://pubmed.ncbi.nlm.nih.gov/31622071