̒⥎⥁℧♠⣜֯ 㧙 ֯ݶ ٨ᯂॺⅰ֯ ಞ ב 䢬ٛ ሱ⻠㑅㕵٨Ǎ⡾㧙֯ ᖾ䢬ឱ〤् 㞘⓺ǎ ॺᑜ$3*S13/$BT9ᇤ⻐全् ᐵ༄ ⅰཅ⒢۠ 大⿈ឹ ╥㑢֯ ᖾᇤ⻐㟘發നᙋ 中䢬㬟ೡ⦾༴㘱 ژ ḳᕔ㡉Պ܅㐫 ⻋ε䢬ྲ ̜ ༴⏲ᇤᑓ發ൠന 㦕㇒㕷Ᏻቆǎനᙋ⡾ᴲ$3*S13/$BT9 ᇤ⻐् ⛵㎊ᅞ㟘發䢬㟘發Ͼኖ٨ ಾ成3/"ᑜ$3*S13/$BT9ⅰ ᑓᑚᧈ䢬㐔ཅ⒢˞₅首個٨ಾ成 $3*S13/$BT9̿ 㧙全् ♲ᐵ༄䢬ྉ 成⏲ಾǍ ۽ 㤖ⅰ$3*S13/$BT9ᇤ⻐大 ⿈ឹ ╥㑢ᐨᎭ֯ ᖾ☲⚕ǎ㬟ೡㆯㆺཅ ⒢㑕ᅞ$3*S13/DBT9㭗㐜㕵╥㑢ⅰᐨ Ꭽ֯ ᖾ☲⚕ǎゔ㧋♲ᅞ ݶ ᏼ㐫 נ ᕧཅ ⒢ⅰTi3/"ᐵ༄㭗㐜㕵╥㑢㭓☲䢬ཅ⒢ $3*S13/$BT9㭓☲↷ឱḳ༄〲〘Ǎഭ ᵦ♲〲Ǎ૦ಡᖱ㑢Ǎឺ ᕲ㕵⌒֯ ᖾᐨύឹ় 䢻 ܒ ᒿ䢬ധᐨᎭㇰዀⅰဓႰ ཙՄ㬟〲〘ᬚ㦵䢬⿼ ݶ ᘪᢩ ☲⚕ 㬟Ѯǎ laboratory performs data analysis, including expression quantification, cluster analysis, and marker gene identification, to explore the classification and possible molecular mechanisms underlying differentiation of breast tumour cells of rats. In the project of library construction of whole genome and high-throughput screening based on CRISPR/Cas9, Zhang’s laboratory and RiboBio Co., Guangzhou began cooperation which is supported by a Science Innovation and Development Grant of the Guangzhou government. The project focuses on the development of application using CRISPR/Cas9 gene editing and accessible synthetic chemistry for RNA synthesis in CRISPR/Cas9 editing, so that it progressively builds the world’s first human genome library which constitutes a scientific and reliable system of CRISPR/Cas9 high-throughput screening analysis, to support the mass application and industrialisation of CRISPR/Cas9 technology. Zhang’s laboratory is responsible for developing data analysis platform for high-throughput screening with CRISPR/ Cas9 editing. More specifically, our laboratory employs and improves the early high-throughput screening system with siRNA library, and designs mathematical models for target library, reference setup, microplate selection and sample quantification compliant with CRISPR/Cas9 editing. Also, we introduce quality control on data in experimental design to reduce systemic errors. ᔧ⬷䢬Ҁ༏⏲ಾಾ㡕ᐑእǍ ژ മຨ䢬⟜२⚕〘 ږ ᕐᕐ ݶ २㢂⚕〘ಾᕐ成䢬研㦦৴ ᩯ⯭㕕ℼ̿ 智ᄏǍ㭗㐜㕵╥㑢Ǎ् ⻠় Ǎ☃ᬞ㕕ℼǍᐨತ㕕ℼǍ㭗㐜㕵् ᫎǍ⦦ ḳ大ᐨᎭ㕕̿ 智ᄏ㟘發⓺૦個㦦৴ǎ 㕷К䢬ᔧ⬷ᐑእⅰ ژ 䢬έ˷⾾ㆯㆺ⦦㕕ಾ大ᐨᎭ֯ ᖾⴵύ䢬നᏽᑚ ᳤ܗ 㐥❼↮ᫎύ ᐨᎭॺ ⃚ܻݩ 中ⅰᅞ⦾研䢬ኼ࣮ ಾ⠗⦾㤔⛨လᑚᧈഭ⃓⃚ ⅰ㦞ᫎ⦾〹ᑘǎ Douglas Zhang is a professor in the Faculty of Health Sciences, University of Macau. He is a fellow of the American Statistical Association and a member of the International Statistical Institute. His research interests include medical artificial intelligence, highthroughput screening, phenomics, precision medicine, digital medicine, high-throughput sequencing, and big data and artificial intelligence in clinical medicine. Jin Yu is a third-year PhD student at the University of Macau supervised by Prof Douglas Zhang. She is responsible for the analysis and processing of big data in clinical medicine. Her specialisation is the application and studies of continuous monitoring of physiological data in respiratory diseases, as well as the prediction and diagnosis of diseases by machine learning and nonlinear methods. ಾ⻐研 • ACADEMIC RESEARCH 澳大ᑓゆ • 2019 UMAGAZINE 20 67
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