26 March 2018
UPH Science-Tech Colloquium: Discussing the Benefits of Machine Learning in Biotechnology
On Friday 23th March 2018, Faculty of Science and Technology of Pelita Harapan University (FaST) held The Science-Tech Colloquium. This session’s topic is ‘Machine Learning for Biology’ which is delivered by Michael Gotama, an alumnus who is also a lectur
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Michael Gotama is giving the Machine Learning material kepada to the Lecturers
 

On Friday 23th March 2018, Faculty of Science and Technology of Pelita Harapan University (FaST) held The Science-Tech Colloquium. This session’s topic is ‘Machine Learning for Biology’ which is delivered by Michael Gotama, an alumnus who is also a lecturer in UPH Biotechnology.

 

  

The Science-Tech Colloquium itself is a monthly event of the Faculty of Science and Technology (FaST) that has been held since 2011 by departments of science and technology area. This session is the second session in 2018, that previously in February, it was held by Mathematics Department, discussing about dynamic system.

 

 

This event was attended by approximately 30 participants who consist of FaST UPH lecturers. Through this program, the lecturers of FaST gathered to discuss scientific topics.

According to Dr. Henri P. Uranus, the coordinator of the colloquium, this scientific event is expected to be a forum for information sharing and for colleagues to know each other research so that it may become a cooperation for research of FaST departments and increase scientific culture among the academical civitas of FaST.

 

 

The Colloquium of Biotechnology Department discussed about the Machine Learning, a computer algorithm which is designed to predict or classify the data. According to Michael, this concept is a common concept in the computer field and it has been used for various interests.

 

 

Michael added that previously the machine learning has been widely used for public purpose, such as: stock price prediction, camera technology on mobile-phone, cars without drivers and etc. But the interesting point is this computational function can also be applied in Biology field. According to Michael, the correlation between these two is both of them relate to the big data, where machine learning is working based on the big data and Biotechnology is also a knowledge that relate to molecular that produces big data. With this concept, people in Biotechnology field can use the data for further various benefits.

 

 
 
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“The example of this machine learning concept using is it can be used for drug screening process to produce the more targeted medicines. This benefit has been proven by the discovery of new medicines for malaria through artificial intelligence and utilization of machine learning concept. Besides that, it also relates to an enzyme creation. This machine learning can be used to search for the prediction of the optimum condition of an enzyme. Without this machine learning, the process for enzyme testing will require more time, more budget and expensive laboratory tools that is supportable. With this machine learning, the sequences data of an essence of enzyme-forming, for example amino acids will be converted to be coding for data and evaluation.” said Michael.

 

 
 
 A public lecture with this material is considered important because Michael thinks that with the big data trend, the concept of machine learning becomes very relevant to be developed. According to Michael, both students and lecturers who participate in the process of data management must know the computer method so that the processing and conclusion from the data can be more effective.(mt)
 
 
 
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