Computational thinking in the era of big data biology

It is fall again, and another class of students has arrived in the Watson School of Biological Sciences at Cold Spring Harbor Laboratory (CSHL). Building on the lab's 100-year history as a leading center for research and education, the Watson School was established in 1998 as a graduate program in biology with a focus on molecular, cellular and structural biology, and neuroscience, cancer, plant biology and genetics. All students in the program complete the same courses, centered around these research topics, with an emphasis on the principles of scientific reasoning and logic, as well as the importance of ethics and effective communication. Three years ago the curriculum was expanded to include a new course on quantitative biology (QB) and I, along with my co-instructor Mickey Atwal and other members of the QB program, have been teaching it ever since

Computational Creativity

In: Encyclopedia of Systems Biology, W. Dubitzky, O. Wolkenhauer, K-H Cho, H. Yokota (Eds.), Springer 2011Understanding brain processes behind creativity and modeling them using computational means is one of the grand challenges for systems biology. Computational creativity is a new field, inspired by cognitive psychology and neuroscience. In many respects human-level intelligence is far beyond what artificial intelligence can provide now, especially in regard to the high-level functions, involving thinking, reasoning, planning and the use of language. Intuition, insight, imagery and creativity are important aspects of all these functions

Algorithms in nature: the convergence of systems biology and computational thinking

Biologists rely on computational methods to analyze and integrate large data sets, while several computational methods were inspired by the high-level design principles of biological systems. This Perspectives discusses the recent convergence of these two ways of thinking

Knowledge Level and Self-Confidence on The Computational Thinking Skills Among Science Teacher Candidates

The trending topic in today's education is computational thinking skills which are used to help to solve complicated problems easier. This study aims to identify the level of knowledge and self-confidence of science teacher candidates (physics and biology) on computational thinking skills. The survey research design was used through a mixed-method approach by combining quantitative and qualitative approaches. The quantitative study involved 1016 randomly selected groups of science teachers while in the qualitative study, eight science teachers were chosen based on the scores obtained from the quantitative study. The questionnaire was used as a quantitative data collecting technique to analyze descriptive statistics. Then, an interview was used as the qualitative data collecting technique and was analyzed through theme creation. The findings show that science teacher candidates have a high level of knowledge and self-confidence. The implication of this study is very important for teacher candidates because computational thinking can help to facilitate problems solving in everyday life. Teacher candidates need to be given knowledge and understanding of computational thinking skills, to have readiness and self-confidence in facing the challenges of the learning in the 21st-centur

All biology is computational biology

Here, I argue that computational thinking and techniques are so central to the quest of understanding life that today all biology is computational biology. Computational biology brings order into our understanding of life, it makes biological concepts rigorous and testable, and it provides a reference map that holds together individual insights. The next modern synthesis in biology will be driven by mathematical, statistical, and computational methods being absorbed into mainstream biological training, turning biology into a quantitative science.Cancer Research UK (grant number C14303/A17197)

Integrating Evolutionary, Cultural, and Computational Psychiatry: A Multilevel Systemic Approach

This paper proposes an integrative perspective on evolutionary, cultural and computational approaches to psychiatry. These three approaches attempt to frame mental disorders as multiscale entities and offer modes of explanations and modeling strategies that can inform clinical practice. Although each of these perspectives involves systemic thinking, each is limited in its ability to address the complex developmental trajectories and larger social systemic interactions that lead to mental disorders. Inspired by computational modeling in theoretical biology, this paper aims to integrate the modes of explanation offered by evolutionary, cultural and computational psychiatry in a multilevel systemic perspective. We apply the resulting Evolutionary, Cultural and Computational (ECC) model to Major Depressive Disorder (MDD) to illustrate how this integrative approach can guide research and practice in psychiatry

Mathematical Modelling and Computer Simulations in Undergraduate Biology Education

A course in computational biology that introduces undergraduate biology students to mathematical modelling and computer simulations is described. Spreadsheets offer the perfect environment to introduce our biology students to computational thinking and the increasing role that computer simulations are playing in biology research. Here, we detail the spreadsheet modelling of some of the simulations covered in the course; the Lotka-Volterra predator-prey model, a cellular automaton model of tumor growth, and a model of an infectious disease outbreak. The experience of implementing computational biology simulations in a spreadsheet environment encourages and enables our biology students to use computer simulations and spreadsheets more in their future research, and makes our students more comfortable when interpreting scientific literature that pertains to computational biology research. These are important skills that our biology students will need in their future careers as researchers and scientists

On the Role of Geometry in Formal Design

In recent decades, new methodologies have emerged in architectural design that exploit the computer as a design tool. This has generated a varied set of digital skills and a new type of architectural knowledge. This means, architecture is taking part in an “intellectual revolution [that] is happening all around us, but few people are remarking on it. Computational thinking is influencing research in nearly all disciplines, both in the sciences and the humanities. It is changing the way we think.” i A good example of such reshaping of discipline-immanent thinking by means of computation is the paradigmatic shift in sciences like physics or biology caused by the introduction of the computer as the primary tool for simulating and modelling natural processe