YANG MING  CHIAO TUNG INSTITUTE OF BIOMEDICAL INFORMATICS
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[¥Í¸êºÓ¤h¯Z] 1062[¥ÍÂå¸ê±M°Q(ºÓ¯Z¥Í¸êI)]
Instructors ªL®¶¼y¦Ñ®v¡B¤ý¬ê¶W¦Ñ®v¡B³¯¨ô¶h¦Ñ®v
Location ¦u¤¯¼Ó101±Ð«Ç (Rm. 101, SoRen Building)
Time Monday,13:20-15:10
Website http://video.ym.edu.tw/course/view.php?id=175
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Date Speaker Topic Note
02¤ë26¤é - ³W«h»¡©ú
03¤ë05¤é -
03¤ë12¤é ¸­®aÞ³ Network inference and hypotheses generation from single cell transcriptomic data using multivariate information measures
03¤ë19¤é §õ¨ä®Ù Genomic Analysis of Tumor Microenvironment Immune Types across 14 Solid Cancer Types: Immunotherapeutic Implications
03¤ë26¤é ±iªF²[ Massively parallel digital transcriptional profiling of single cells
04¤ë02¤é ¶À¤d®e Integrative gene network analysis identifies key signatures, intrinsic networks and host factors for influenza virus A infections
04¤ë09¤é ¦¶«ß¦w De-novo protein function prediction using DNA binding and RNA binding proteins as a test case
04¤ë16¤é - ´Á¤¤¦Ò¶g
04¤ë23¤é - ©Ò¤W¬¡°Ê-¤jreview
04¤ë30¤é ¶ÀÞmÚ¬ The paradox of HBV evolution as revealed from a 16th century mummy
05¤ë07¤é ½²©sªÚ
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05¤ë21¤é §õªÃ¿« Integrative genomic analysis implicates limited peripheral adipose storage capacity in the pathogenesis of human insulin resistance
05¤ë28¤é ¶ÀÍk²E
06¤ë04¤é - ©Ò¤W¬¡°Ê-©ç·Ó¤Î°eÂÂÀ\·|
06¤ë11¤é ¶À¤å¼Ý(°ò¬ì©Ò) Amyloidogenic motifs revealed by n-gram analysis

[¥Í¸êºÓ¤h¯Z] 1062[¥ÍÂå¸ê±M°Q(ºÓ¯Z¥Í¸êII)]
Instructors ¶À«ÛµØ¦Ñ®v¡B·¨¥Ã¥¿¦Ñ®v¡BÁéÖö¤è¦Ñ®v
Location ¦u¤¯¼Ó104±Ð«Ç (Rm. 104, SoRen Building)
Time Monday,13:20-15:10
Website http://eeclass.ym.edu.tw/
Date Speaker Topic Note
02¤ë26¤é - ½Òµ{²¤¶¤Î³W½d
03¤ë05¤é - ·Ç³Æ¶g
03¤ë12¤é - ·Ç³Æ¶g
03¤ë19¤é §d¹Å¿o Playing Atari with Deep Reinforcement Learning
03¤ë26¤é ¸­ÓVüQ An Immunogenic Personal Neoantigen Vaccine for Melanoma Patients
04¤ë02¤é ±i­ì¹Å Tumor Mutational Burden as an Independent Predictor of Response to Immunotherapy in Diverse Cancers
04¤ë09¤é ªô§´­b Mutational and putative neoantigen load predict clinical benefit of adoptive T cell therapy in melanoma
04¤ë16¤é - ´Á¤¤¦Ò¶g
04¤ë23¤é - ©Ò¤W¬¡°Ê-¤jreview
04¤ë30¤é ©P­³§Ê The research on gene-disease association based on text-mining of PubMed
05¤ë07¤é ¿àµÎ´@ Predicting effective microRNA target sites in mammalian mRNAs
05¤ë14¤é ³¯¾_ Human fetal dendritic cells promote prenatal T-cell immune suppression through arginase-2
05¤ë21¤é ¤ý¹Å·| Cell type atlas and lineage tree of a whole complex animal by single-cell transcriptomics
05¤ë28¤é ¤ýµYµ¾ Coordinates and intervals in graph-based reference genomes
06¤ë04¤é - ©Ò¤W¬¡°Ê-©ç·Ó¤Î°eÂÂÀ\·|
06¤ë11¤é ¦¶´¼¼w

[Âå¸êºÓ¤h¯Z] 1062[¥ÍÂå¸ê±M°Q(Âå¸êºÓ³Õ)]
Instructors ±i³Õ½×¦Ñ®v¡B§Å©[«~¦Ñ®v¡B§õ°ê±l¦Ñ®v
Location ¦u¤¯¼Ó102±Ð«Ç (Rm. 102, SoRen Building)
Time Monday,13:20-15:10
Website
Date Speaker Topic
02¤ë26¤é - ½Òµ{²Ä¤@¤Ñ¤W½Ò¡A¤½§G³ø§i¤è¦¡¤Î¶¶§Ç
03¤ë05¤é - ©âÅÒ¿ïÃD¥Ø¡B³ø§i¤é´Á
03¤ë12¤é ²Ä1²Õ³ø§i¡G
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POPLIN, Ryan, et al. Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning. Nature Biomedical Engineering, 2018, 1.
03¤ë19¤é ²Ä1²Õ°Q½× POPLIN, Ryan, et al. Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning. Nature Biomedical Engineering, 2018, 1.
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POPLIN, Ryan, et al. Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning. Nature Biomedical Engineering, 2018, 1.
04¤ë02¤é ²Ä2²Õ°Q½× POPLIN, Ryan, et al. Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning. Nature Biomedical Engineering, 2018, 1.
04¤ë09¤é - ²M©ú«á¼u©Ê¥ð®§
04¤ë16¤é - ´Á¤¤¦Ò¶g
04¤ë23¤é - ©Ò¤W¬¡°Ê-¤jreview
04¤ë30¤é ²Ä3²Õ³ø§i¡G
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BANJAR, Haneen, et al. Intelligent Techniques Using Molecular Data Analysis in Leukaemia: An Opportunity for Personalized Medicine Support System. BioMed research international, 2017, 2017.
05¤ë07¤é ²Ä3²Õ°Q½× BANJAR, Haneen, et al. Intelligent Techniques Using Molecular Data Analysis in Leukaemia: An Opportunity for Personalized Medicine Support System. BioMed research international, 2017, 2017.
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LEE, Choong Ho; YOON, Hyung-Jin. Medical big data: promise and challenges. Kidney research and clinical practice, 2017, 36.1: 3.
05¤ë14¤é ²Ä4²Õ°Q½× LEE, Choong Ho; YOON, Hyung-Jin. Medical big data: promise and challenges. Kidney research and clinical practice, 2017, 36.1: 3.
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COHEN, Joshua D., et al. Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science, 2018, eaar3247.
05¤ë28¤é ²Ä5²Õ°Q½× COHEN, Joshua D., et al. Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science, 2018, eaar3247.
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ROSS, C.; SWETLITZ, I. IBM pitched its Watson supercomputer as a revolution in cancer care. It¡¦s nowhere close. Statnews, 2017.
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06¤ë11¤é ²Ä6²Õ°Q½× ROSS, C.; SWETLITZ, I. IBM pitched its Watson supercomputer as a revolution in cancer care. It¡¦s nowhere close. Statnews, 2017.