Topic modeling is an Information Retrieval (IR) technique that discovers representative topics from a collection of documents. Thus, we expect that logically related words will co-exist in the same document more frequently than words from different topics. For example, in a document about the space, it is more possibly to find words such as: planet, satellite, universe, galaxy, and asteroid. Whereas, in a document about the wildlife, it is more likely to find words such as: ecosystem, species, animal, and plant, landscape. But why text classification is so useful? In this blog post, we try to explain the importance of topic modeling and its use in software engineering.
I am very pleased to introduce the June issue for XRDS on computational biology. I had the privilege to work as Issue Editor for this issue alongside Guest Editor Cristina Pop, who recently received her Ph.D. from Stanford University.
Computational biology is ubiquitous. Every modern bioscience lab relies on computational biology and bioinformatics techniques to some extend, whether for gene and protein sequencing or data storage. Moreover, advances in computational biology techniques allow researchers to gain deeper insights into biological mechanisms, simplify lab-bench methods, and develop more reliable and sophisticated methods for diagnosis and clinical applications. Computational biology drives biological research and even bounds the types of questions that researchers and clinicians can ask. This is why it is such an exciting and rapidly growing area of computer science.
Image from Flickr Libertas Academica, Creative Commons
We chose to structure this issue loosely around five stages of biological experimentation that make significant use of computational biology. These stages are: data gathering, data storage, refining and visualizing data, modeling data, and drawing conclusions from data. These may sound like standard steps in most data science workflows, and that’s because they are. With techniques like next generation sequencing and electronic patient records producing biological and healthcare data in ever-greater volumes, computational biology leverages many big data approaches and applies them to scientific data. The field of computational biology focuses on developing algorithms and techniques well attuned to biological data in particular.
Our features and interviews present several different angles into some of the most recent advances in computational biology. Russ Altman, Director of Biomedical Informatics at Stanford University, discusses his role in leading an interdisciplinary research program as well as his work in personalized medicine and pharmacogenetics, the use of genetic data in selecting and prescribing drugs.
Many of this issue’s articles focus on drawing inferences from large-scale studies and datasets using computational methods. David Heckerman and Christoph Lippert of Microsoft Research describe machine-learning techniques for mapping genetic differences to phenotype in large-scale genetic studies known as genome-wide association studies. Their work includes methods for disentangling correlation and causation when genetic differences in distinct populations also coincide with phenotypic variations.
We profile Suchi Saria of John Hopkin’s University, whose many valuable contributions to research and industry include developing techniques for predicting patient outcomes and treatments from electronic records. She discusses challenges and ongoing research in this area as well as her contributions to a variety of startups.
Also, we provide insights on how modern biology uses computer simulations. We speak with Vijay Pande, Director of Folding@Home, on using software to simulate protein folding. Folding@home is a widely used protein folding software program, that lets users anywhere in the world, via the Internet, donate a portion of their computer’s CPU to solving protein folding problems.
Marina Sirota and Bin Chen of the University of California at San Francisco write about computational and statistical techniques for drug discovery, which greatly increase the speed and cost at which new drug designs can be identified and then developed and tested at the bench.
This issue also introduces some cutting-edge techniques for computational biology. Karen Sachs of the Stanford School of Medicine and Tiffany Chen, Director of Informatics at Cytobank, Inc., discuss computational approaches in single-cell measurement techniques. These techniques are extremely powerful – traditional medical measurements often involve patient-wide approaches, such as average measurements in blood tests. Single-cell measurements are valuable in studying diseases like cancer, where individual cells can wreck havoc on the body.
Malay Bhattacharyya of the Indian Statistical Institute contributes on dietomics, which uses computational techniques the way personalized medicine might to make predictions about what individuals should eat for improved health and disease avoidance.
Adam A. Smith of the University of Puget Sound writes about using Markov models to model mouse vocalizations, which can be used to intuit a mouse’s mental state and may provide models for human mental disorders like schizophrenia and autism.
Sarah Aerni, Hulya Farinas, and Gautam Muralidhar of Pivotal Software outline their work in data storage, an important aspect of managing and using computational biology data.
While these feature articles present only some of the manifold exciting areas of computational biology research, we hope this issue presents a diverse range of ideas for our readers, from how computers influence large-scale studies and healthcare decisions to how they reveal the microscopic details of protein folding and subcellular structure and function.
Our Departments Section includes some exciting articles, from a discussion with Sriram Kosuri of the University of California, Los Angeles, whose paving the way forward in the field of DNA computing and storage, to tips on how to write an effective scientific paper.
Working for several years in a biochemistry lab myself, both at the bench and on the computational side, I witnessed just how much technological advances transformed the types of biological questions we could ask. We hope that these perspectives on some groundbreaking approaches to computational biology help spark your own questions that may one day help us solve pressing biological problems, or at least pique your interest in the exciting computer science subfield that is computational biology.
Most people maybe think that software engineers are only coders that develop and maintain applications, systems, and infrastructures. This is not false. But, software engineers are also responsible for the assessment and improvement of the source code itself, based on specific metrics and techniques. This post briefly discusses how software engineering can evaluate modern software systems.
Given that usually the compiler does not complain about the coding style of a program (i.e. missing white spaces, indentation, long lines of code, name conventions, and comments), developers care only for the functionality of their programs and not for the maintainability. However, this can be harmful for the understanding and maintenance of modern software systems. This post discusses the importance of writing programs based on specific coding guidelines.
The last day of CHI in Seoul left everyone with that bittersweet taste of ending mixed with nostalgia and, was still a great day to see great research!
For me, the day started off with Augmented & Virtual Reality in the Real World (VR is here to stay!) and followed onto Interacting with Floors & Situated Displays (have you seen BaseLase? Check that video or the image below, quite an interesting approach to a portable large screen).
The last session of the CHI spectrum this year was Speech & Auditory Interfaces, which focused on lots of abstract sound UIs — really nice works there, go check it out if you are into sonic interaction. After this it was time for the closing keynote, by pop musician Psy. A local hero in mainstream Korea for obvious reasons and a humble speaker that decided to allude to his career build up and share lots of his personal insights with the HCI audience. At last, the next CHI was announced… see you all in San Jose for CHI’16!
Disclaimer: CHI is a multiple track conference, with a dozen of parallel sessions, so the truth is: I’ve never felt a bigger desire for ubiquity (the great thing is that this year things are being recorded and will be on the ACM Digital Library soon. Thanks to the SVs for filming the talks!)
In the third day of CHI a lot of attention was given to future interfaces that attach directly to the users’ body. The great thing is that being a research conference, CHI goes much further than the wearables and smartwatch industry so researches here presented developments in haptic wearables that control your muscles (an example of that is my own work presented this year), rings that notify you using temperature (Notiring), interactive tattoo-like stickers that allow you to interact directly onto your skin (iSkin), and even nail covers that allow you to secretly interact with your technology (NailO)!
Some future interfaces that live on your body: a bracelet that reads and writes to your muscles and a Nail interface:
Of course the CHI community is not only about new hardware but a much broader and grounded on the understanding of Computing and Human Factors. This means over the past three days we’ve seen many explorations and studies that provide a deeper understanding of the world of ergonomics, crowd-sourcing, collaborative work, interaction techniques, and human cognition too.
Furthermore, this year there has been an amazing body of work that takes the CHI community to the real world as discusses important, real-world questions, such as “Encouraging Energy Conservation”, “Gender inclusive Software” and a great focus (as always) in making HCI (and CHI) accessible to all people!
The second day of CHI started off quite happily for me as I was presenting my new work on Proprioceptive Interaction (sorry for shameful link!) at the muscle-interfaces session which was very interesting. In this session researchers discussed how future muscle sensing can be increased for higher resolution input or even by combining multiple technologies such as EMG and MMG. After that I could relax a bit and attend more interesting sessions on a variety of different topics! Later on, there were sessions on smartwatch interactions, which demonstrate that we are no longer in the smartwatch hype but instead we are really in the wearables era! Great to see that research are also thinking already beyond-wearables, skin interaction, smaller devices, haptic wearables and so forth, which will be presented tomorrow (Day 3, check the post too): looking forward to that!
Later on I attended a very interesting and futuristic session on 3D fabrication which in the same vein, demonstrates that we are beyond 3D printing only in the maker community but also in the HCI community! In this session researchers showed their new ideas for the world of fabrication, such as 3D printing using soft fabric (great for plushy-toys!), check their video here.
The day ended with the job fair… a great opportunity to the more junior people to find internships and perhaps a new position either at industry or research labs!
The first day of CHI started with a great opening plenary by Lou Yongqi (check keynotes here and yes, check out WHO is the closing plenary!), which came forward and highlighted the importance of Sustainability in research! Followed by an amazing program of novel technology (think Virtual Reality!), human augmentation (check this totally new way of embodying another person by Prof. Rekimoto), user studies (“Understanding and evaluating User Performance”), and understanding of elder users (“Designing for 55+”) and communities (a great session on Activism in Wikipedia, one on Privacy and one on the “Maker Community”)!
Also this was the day of the video-showcase, which is a non-academic venue in which authors can submit their videos for further appreciation. It is an amazing opportunity to great a glimpse of CHI by sitting in the theater and watching great research in motion. This year’s winner was the Transform project by the MIT Media Lab (see it here), from which one of the authors is our dear editor Sean Follmer, so congrats to him and his team!
For over 30 years, the CHI conference has been the top-tier venue for the developments in the field of Human Computer Interaction (HCI). CHI has been truly a place to share ground-breaking research and novel ideas into the ever evolving interaction between humans and machines. This year the conference takes place in the vibrant city of Seoul, in the heart of South Korea!
Unlike most conferences in HCI, CHI is has a broad spectrum of disciplines: computer science, cognitive psychology, design, social science, human factors, artificial intelligence, graphics, visualization, multi-media design and many others; making it a huge conference: this year, at the opening keynote, were more than 2800 researchers!
CHI is an important venue not just for professors and senior researchers but primarily for the younger ones, such as myself. CHI is a prime moment to reflect, learn and observe the field. There is no rupture, innovation, ground-breaking thoughts without a clear understanding of where HCI is right now.
If you are not familiar with CHI or even with HCI, don’t be afraid! The field is very understandable to non-experts as people try to be as clear as possible, because CHI itself is a mix of the aforementioned and very idiosyncratic disciplines; so we keep things lively with videos, animations and short summaries. Have a look at the program and you’ll find many videos to watch. In fact, just to make things really exciting, this year the chairs created a youtube playlist that allows you to browse through this massive program
in the comfort of your laptop (wherever you are!). If you are more into the academic reading, then you’ll be happy to know that at CHI the papers are immediately published during the conference, so you can already access them through the ACM Digital Library!
In my previous post, I discussed some current and ongoing research on effective pedagogical approaches to STEM education. The problems in STEM education have gained much attention recently due to the growing gap between demand and skill in American STEM jobs, likely due at least in part to lack of interest or discouragement among American students. Continue reading