[Tea Talk] Maksym Korablyov (MIT) Thr June 7 2018 2:00PM AA3195
Sorry for the delay but this week we have *Maksym Korablyov * from * MIT * giving a talk on *Thursday June 7 2018* at *2:00PM* in room *AA3195. *This is usually the learning agents' reading group slot so shoutout to them for letting me have this slot and again to Dima for helping put this together. Maksym is interested in meeting with people to discuss RNNs for structural prediction, conditional feature extraction, and 3D object alignment, and also other applications of deep learning to chemistry. Want to meet with him? Sign up here <https://calendar.google.com/calendar/selfsched?sstoken=UVBVTVF0X25Nd09LfGRlZmF1bHR8ZWQ5MmNlYWMxODI4OWVkNmUzNGU3OTE4ZDExMGI0YTk> Can't make it? Email me and I'll set something up! Note: There will be no streaming so come in person! If your *deep learning* code is *breaking bad*, take a break and come to this talk! Michael *TITLE* A few steps towards molecule google *KEYWORDS *deep learning chemistry, deep learning theory *ABSTRACT* Commonly used search engines such as Google can retrieve relevant entries with high speed and accuracy from spaces as big as 10^12 - the number of words in the Internet. Search algorithms that could address the space of 10^80 - 10^100 drug-like molecules are not yet publicly available. The world’s combined effort of pharmaceutical companies (experimental + computational) is ~10^15 molecules/year with 30-50 new drugs found. In this talk I will 1: give some numerical estimates of the value of unexplored chemical space. 2: provide some intuition why all possible molecules could be mapped to a low-dimensional manifold and which families of functions might efficiently describe such mapping. 3: show some empirical results of the search in 10^80. 4: present an algorithm for partial flexible shape match (drug + protein) that we have developed recently. *BIO* Maksym Korablyov is a graduate student advised by Dr. Joseph Jacobson at Massachusetts Institute of Technology, Media Lab. Prior to MIT, Maksym was a Fulbright Fellow at Harvard Medical School with Dr. Gil Alterovitz for one year. Maksym holds MS in Bioinformatics from Georgia Institute of Technology where he developed a series of potent antiviral inhibitors jointly with Dr. James Gumbart and Dr. Raymond Schinazi.
Starting in 5 minutes! On Wed, 6 Jun 2018 at 10:29 Michael Noukhovitch <mnoukhov@gmail.com> wrote:
Sorry for the delay but this week we have *Maksym Korablyov * from * MIT * giving a talk on *Thursday June 7 2018* at *2:00PM* in room *AA3195. *This is usually the learning agents' reading group slot so shoutout to them for letting me have this slot and again to Dima for helping put this together.
Maksym is interested in meeting with people to discuss RNNs for structural prediction, conditional feature extraction, and 3D object alignment, and also other applications of deep learning to chemistry. Want to meet with him? Sign up here <https://calendar.google.com/calendar/selfsched?sstoken=UVBVTVF0X25Nd09LfGRlZmF1bHR8ZWQ5MmNlYWMxODI4OWVkNmUzNGU3OTE4ZDExMGI0YTk> Can't make it? Email me and I'll set something up!
Note: There will be no streaming so come in person!
If your *deep learning* code is *breaking bad*, take a break and come to this talk! Michael
*TITLE* A few steps towards molecule google
*KEYWORDS *deep learning chemistry, deep learning theory
*ABSTRACT* Commonly used search engines such as Google can retrieve relevant entries with high speed and accuracy from spaces as big as 10^12 - the number of words in the Internet. Search algorithms that could address the space of 10^80 - 10^100 drug-like molecules are not yet publicly available. The world’s combined effort of pharmaceutical companies (experimental + computational) is ~10^15 molecules/year with 30-50 new drugs found. In this talk I will 1: give some numerical estimates of the value of unexplored chemical space. 2: provide some intuition why all possible molecules could be mapped to a low-dimensional manifold and which families of functions might efficiently describe such mapping. 3: show some empirical results of the search in 10^80. 4: present an algorithm for partial flexible shape match (drug + protein) that we have developed recently.
*BIO* Maksym Korablyov is a graduate student advised by Dr. Joseph Jacobson at Massachusetts Institute of Technology, Media Lab. Prior to MIT, Maksym was a Fulbright Fellow at Harvard Medical School with Dr. Gil Alterovitz for one year. Maksym holds MS in Bioinformatics from Georgia Institute of Technology where he developed a series of potent antiviral inhibitors jointly with Dr. James Gumbart and Dr. Raymond Schinazi.
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participants (2)
-
Dzmitry Bahdanau -
Michael Noukhovitch