研究課題/領域番号 |
20K12043
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研究種目 |
基盤研究(C)
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配分区分 | 基金 |
応募区分 | 一般 |
審査区分 |
小区分62010:生命、健康および医療情報学関連
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研究機関 | 奈良先端科学技術大学院大学 |
研究代表者 |
AMIN MD.ALTAFUL 奈良先端科学技術大学院大学, 先端科学技術研究科, 准教授 (30379531)
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研究期間 (年度) |
2020-04-01 – 2024-03-31
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研究課題ステータス |
交付 (2022年度)
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配分額 *注記 |
3,250千円 (直接経費: 2,500千円、間接経費: 750千円)
2022年度: 1,040千円 (直接経費: 800千円、間接経費: 240千円)
2021年度: 910千円 (直接経費: 700千円、間接経費: 210千円)
2020年度: 1,300千円 (直接経費: 1,000千円、間接経費: 300千円)
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キーワード | Antibiotic compounds / Natural products / Machine learning / Jamu formulas / TCM formulas / Antimicrobial / Traditional Medicines / Lasso regression / Deep learning / Machine Learning / Graph Clustering / Random Forest / Chemoinformatics / Antimicrobials / Natural Products |
研究開始時の研究の概要 |
Antimicrobial agents are drugs that can kill microorganisms or stop their growth. Widespread overdose and irresponsible usage of antibiotics in clinical practicees for both human and livestock has resulted in resistance of bacteria to antimicrobial agents. Such multidrug-resistant (MDR) bacteria are recently called as Superbugs. MDR bacteria poses global problems with the threat of the reoccurrence of a situation of the pre-antibiotic era and increased cost of healthcare services. This work will search antimicrobial agents/drugs among natural products by utilizing mainly chemoinformatics.
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研究実績の概要 |
Antimicrobial agents are drugs that can kill microorganisms or stop their growth. massive imprudent usage of antibiotics in clinical practice for both human and livestock has resulted in resistance of bacteria to antimicrobial agents. Our research focused on finding natural antibiotic compounds based on traditional medicine formulas. We applied various machine learning algorithms such as Lasso regression, Random Forest and XGBoost, deep learning to Jamu and TCM formulas aiming to finding natural antibiotic plants and compounds. Based on our research in the current fiscal year, we published two papers in journals with reasonable impact factors. One of the papers published in the journal Antibiotics (Impact Factor 4.94) identified antibiotic plants based on Jamu formulas. Another paper published in the journal Methods (Impact Factor 4.647) found out antibacterial natural compounds based on TCM formulas. We also published two papers in IEEE conferences.
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現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
Our PhD students Mr. Ahmad Kamal Nasution and Mr. Gao Pei helped me a lot for conducting this research
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今後の研究の推進方策 |
Currently we are working on finding natural antibiotic compounds based on Unani formulas. Next, we want make comparison between the results we obtained based Jamu, TCM and Unani formulas. We will make a comprehensive list of promising natural antibiotic compounds and by applying unsupervised clustering we will try to identify the type of mechanisms of actions against bacteria.
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