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X-WR-CALDESC:[21st AIP Open Seminar] Talks by Molecular Informatics Team
X-WR-CALNAME:[21st AIP Open Seminar] Talks by Molecular Informatics Team
X-WR-TIMEZONE:Asia/Tokyo
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TZID:Asia/Tokyo
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DTSTART:19700101T000000
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
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UID:811572@techplay.jp
SUMMARY:[21st AIP Open Seminar] Talks by Molecular Informatics Team
DTSTART;TZID=Asia/Tokyo:20210414T150000
DTEND;TZID=Asia/Tokyo:20210414T170000
DTSTAMP:20260503T223414Z
CREATED:20210315T060011Z
DESCRIPTION:イベント詳細はこちら\nhttps://techplay.jp/event/81157
 2?utm_medium=referral&utm_source=ics&utm_campaign=ics\n\nMolecular Inform
 atics Team (https://aip.riken.jp/labs/goalorient_tech/mol_inf/) at RIKEN 
 AIP\n\nSpeaker 1: Koji Tsuda (10min)\nTitle: Overview of Molecular Inform
 atics Team\nAbstract: \nIn molecular informatics team\, we develop comput
 ational methods for analyzing and developing molecules and materials. We 
 focus on machine learning driven design of new materials and proteins\, a
 nd functional analysis of protein dynamics using the rigidity theory. I i
 ntroduce our activities briefly in this talk.\n\nSpeaker 2: Masato Sumita
  (45min)\nTitle: Informatics driven research for advanced materials based
  on physicochemistry\nAbstract: \nThe development of  nano-technology wid
 ely realized us the effectiveness of controlling materials at the atomist
 ic level. Many studies at the atomistic level are accumulated in physicoc
 hemical theories. However\, the atomistic-level control of materials usin
 g these theories is not easy because of complexity of the atomistic arran
 gement of materials. Machine learning is useful to deal with this complex
 ity. In this seminar\, we will show some successful examples where machin
 e learning compensates physicochemical theories to search or design  mate
 rials.\n\nSpeaker 3: Adnan Sljoka (45min)\nTitle: Rigidity theory of fram
 eworks and graphs with applications to protein structure validations and 
 functional analysis\nAbstract:\nMathematical Rigidity theory stands at th
 e nexus of combinatorics\, geometry\, graph theory and algorithms. Rigidi
 ty theory is concerned with the rigidity and flexibility of structures th
 at are defined by geometric constraints (fixed lengths\, directions etc.)
  on a set of points\, line segments\, polygons\, bodies\, atoms etc. This
  theory has rich historical roots which date back to Euler (1766) and to 
 Maxwell’s studies of mechanical linkages in the 19th century. Over the 
 last few decades\, interest and mathematical developments in rigidity the
 ory have blossomed rapidly\, which is motivated by applications in many a
 reas of science\, engineering and design\, where geometric constraints se
 rve as suitable mathematical models for an assortment of man-made structu
 res (e.g. robots\, mechanisms\, sensor networks\, meta-materials\, and Co
 mputer-Aided-Design software) or natural materials (e.g. biomolecules\, p
 roteins\, and crystals). In this talk I will introduce basic concepts in 
 rigidity theory setting up a combinatorial characterization of rigidity o
 f generic frameworks and graphs. Macromolecules such as proteins are well
  suited for analysis using rigidity theory\, whose functions is delicatel
 y controlled by interplay of rigidity and flexibility. I will briefly hig
 hlight some of my advances in this area\, such as development of a first 
 workable method for validation of NMR protein structures (Nature Communic
 ations 2020) which has larger   implications in protein structure predict
 ion\, fast computational predictions of protein flexibility and dynamics 
 that have provided critical clues and breakthroughs in biological mysteri
 ous like enzyme catalysis (Science 2017\, JACS 2019)\, cell signalling (N
 ature Communications 2018\, Cell 2021)\, antibody-antigen recognition (Fr
 ontiers in Immunology 2018)\, Covid-19 protein motions etc. We also brief
 ly discuss\, time permitting\, some recent work where we seek to combine 
 rigidity theory techniques with search algorithms / reinforcement learnin
 g to better understand complicated disordered protein dynamics events tha
 t are linked to degenerative diseases.\n\n\n\nAll participants are requir
 ed to agree with the AIP Open Seminar Series Code of Conduct.\nPlease see
  the URL below.\nhttps://aip.riken.jp/event-list/termsofparticipation/?la
 ng=en\n\nRIKEN AIP will expect adherence to this code throughout the even
 t. We expect cooperation from all participants to help ensure a safe envi
 ronment for everybody.\n\n
LOCATION:オンライン
URL:https://techplay.jp/event/811572?utm_medium=referral&utm_source=ics&utm
 _campaign=ics
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