
Snapshots from the UC San Diego Jacobs School of Engineering.
Tuesday, July 14, 2009
A Semiconductor Quandary

Monday, July 13, 2009
Science paper "extended introduction" to new Nature Methods paper on Drug Discovery from UC San Diego researchers

Below I have pasted a few reactions and parenthetical comments on this Science paper from one of the co-lead authors on the Nature Methods paper: Julio Ng, a doctoral student in Bioinformatics at UC San Diego.
Also, there is a cool underwater drug discovery photo of one of William Gerwick, one of the Nature Methods authors, here:
http://cse-ece-ucsd.blogspot.com/2009/07/algorithms-answer-hot-or-not-question.html
The link to the original press release is here:
http://www.jacobsschool.ucsd.edu/news/news_releases/release.sfe?id=866
“The Science paper is very pertinent to our work. My impression is that the Science paper is an extended introduction of our paper, explaining the motivation of our work. Of course, we only attempt to automate the characterization of a set of natural products with a very specific structure (cyclic peptides). In the Science paper, they also discuss the potential of polyketides for commercial drugs. However, a main point of the paper is that drugs based on natural products seem to be declining in recent years. One of the reasons for this decline is that the model of natural product screening is not amenable to high-throughput screening (HTS). This is where we want to bring our software to help the high-throughput identification and dereplication of natural products. I really like the concluding sentence where the authors state that it is not that natural products are a dead end from drug discovery, far from it, they are a vast resource that remains unexplored. And I think we would like to provide the means to help achieve this end.”
-Julio Ng, a co-lead author on the Nature Methods paper and a doctoral student in Bioinformatics at UC San Diego.
Some relevant quotes from the Science paper with added comments from Julio Ng, a co-lead author on the Nature Methods paper and a doctoral student in Bioinformatics at UC San Diego.
“A prevailing sentiment in many pharmaceutical organizations is that screening of natural product sources is a difficult effort with a high probability of duplication; that is, the result may be a known compound that cannot be patented.” (This is the problem of dereplication – Julio Ng) [This is Daniel Kane typing now...the "problem of dreplicatioin" is one that the UC San Diego researchers tackled in their Nature Methods paper].
“Clearly the biological resource is there, but access and examination are problematic, especially if there is pressure for a short time frame for discovery of new leads.” (I think mass spectrometry, coupled with computational tools can speed up this process significantly. Mass spectrometry itself has advantages of being high-throughput, require small quantities of the sample, the data is amenable to computational tools for analysis, etc –Julio Ng)
Algorithms answer "Hot or Not?" question for natural compounds

A researcher isolates a natural compound with promising antimicrobial properties from ocean water. But is it a discovery? Or has the compound already been described and patented? University of California, San Diego researchers have invented computational tools that enable researchers to rapidly and economically answer the ‘is it new or not?’ question for promising drug targets.
Scientists will finally be able to rapidly identify and characterize ring-shaped nonribosomal peptides (NRPs)—a class of natural compounds of intense interest due to their potential to yield or inspire new pharmaceuticals. This advance should speed the discovery of natural compounds produced by organisms such as blue-green algae that could lead to new drugs.
This new work will be published online on July 13 in the journal Nature Methods.
Full press release is on the Jacobs School of Engineering web site:
http://www.jacobsschool.ucsd.edu/news/news_releases/release.sfe?id=866

caption for above photo:
Nuno Bandeira (left) and Julio Ng (right) are UC San Diego researchers and co-lead authors on a Nature Methods paper describing computational and experimental advances that enable researchers to quickly and inexpensively determine whether natural compounds collected in oceans and forests are new -- or if these pharmaceutically promising compounds have already been described and are therefore not patentable.
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credit for photo above:Scripps Institution of Oceanography, UC San Diego/ Cameron Coates
caption for photo above:
William Gerwick collects natural compounds in search of new pharmaceuticals. Gerwick is an author on the new Nature Methods paper and a professor with the UC San Diego Scripps Institution of Oceanography Center for Marine Biotechnology and Biomedicine and the UCSD Skaggs School of Pharmacy and Pharmaceutical Sciences. Read about Gerwick’s work to discover drugs and protect Panama’s natural and cultural resources at:
http://explorations.ucsd.edu/Features/2009/Discovering_Diversity/images/07_2009_Feature.pdf
Thursday, July 9, 2009
Robot Learns to Smile and Frown: More Images!

“As far as we know, no other research group has used machine learning to teach a robot to make realistic facial expressions,” said Tingfan Wu, the computer science Ph.D. student from the UC San Diego Jacobs School of Engineering who presented this advance on June 6 at the IEEE International Conference on Development and Learning.
Download the paper at:
Wednesday, July 8, 2009
Shaking Replica of an Historic Masonry Building: Simulating Strong Earthquakes

http://oneiros.sdsc.edu/~neesit/Shing-Englekirk2.jnlp
http://137.110.165.19/appletvid.html
http://oneiros.sdsc.edu/~neesit/Shing-Englekirk3.jnlp
http://twitter.com/UCSDJacobs
Tuesday, July 7, 2009
Robot Learns to Smile
A Calit2 photographer took great photos of the Einstein robot earlier this year:
http://www.flickr.com/photos/calit2/sets/72157614016199411/
the photo credit for any of these robot images on Flikr is:
UC San Diego / Erik Jepsen
A hyper-realistic Einstein robot at the University of California, San Diego learned to smile and make facial expressions through a process of self-guided learning. The UC San Diego researchers used machine learning to “empower” their robot to learn to make realistic facial expressions.
“As far as we know, no other research group has used machine learning to teach a robot to make realistic facial expressions,” said Tingfan Wu, the computer science PhD student from the UC San Diego Jacobs School of Engineering who presented this advance on June 6 at the IEEE International Conference on Development and Learning.
The faces of robots are increasingly realistic and the number of artificial muscles that controls them is rising. In light of this trend, UC San Diego researchers from the Machine Perception Laboratory are studying the face and head of their robotic Einstein head in order to find ways to automate the process of teaching robots to make realistic facial expressions. Read the full story here.
Monday, July 6, 2009
Engineering Undergrads are International Researchers

There are 24 Jacobs School undergrads spread across the Pacific Rim and India right now. The students are working in research laboratories and at the same time getting to enjoy life as a student studying abroad.
If you are an undergrad or prospective undergrad, this could be you in the next year or two. Summaries of the student projects and their exciting locations listed here on the Jacobs School site.
Calit2's web story includes reactions from students who participated in past years.
Spanish translation of the Calit2 story is linked here.
Visit the PRIME site here (Pacific Rim Undergraduate Experiences)
