Computational biology can be considered a supradisciplinary field of knowledge that merges biology, chemistry, physics, and computer science into a broad-based science that is important to furthering our understanding of the life sciences. Although a relatively new area of research, it is recognized as a crucial field for scientific advancement in developing countries. This Perspective introduces our vision of the role of computational biology in biomedical research and teaching in Cuba. Except where individuals are directly quoted, any opinions expressed herein should be considered those of the authors. (For author information, see Box 1.) The challenge for Cuba was to initiate this new field of research and development without existing expertise. In addition, we had to face the same problems experienced elsewhere in this field—most life scientists were not familiar with the potential of information processing tools, and conversely, computer scientists were unfamiliar with problems facing the life sciences, often brought about by large amounts of new data. Cuba also faced unique problems. As a result of the United States trade embargo, Cuban scientists buy most of their research supplies from Europe. This adds delays and can triple costs, especially for equipment or spare parts that are made only in the US and must be purchased from a third party. In addition, curbs on travel between the US and Cuba isolate Cuban scientists from colleagues and conferences in the United States. Finally, Internet access is also affected by this policy, and Cuban scientists lack fast and efficient access to scientific information from overseas. Despite these drawbacks, Cuban biotech products and activities from biomedical institutes within Cuba have been recognized by other authors [1–4]. Further offsetting these drawbacks, our country has a high educational level, and Cuban universities produce hundreds of new scientists every year. The challenge then is to implement higher education using both the coherence of existing disciplinary education and the means to break down disciplinary walls for students interested in computational biology and other multidisciplinary fields. Since Cuba has scant resources for significant investments in scientific instrumentation, a science such as computational biology that relies mostly on computers, network connectivity, and human resources offers an excellent opportunity. The current challenges facing computational biology research in Cuba are: (1) getting results of direct interest and impact to motivate funding, (2) fostering young leading scientists to sustain present and future research, and (3) using limited infrastructure in the most efficient and productive way. Computational sciences in Cuba were first applied to physics and chemistry in the late 1960s at the University of Havana, with the use of quantum mechanics to model sugar cane derivative molecules [5]. Such an early application of this technology, which was entirely absent in the majority of the world, indicated a new approach to scientific development in a Latin American country. Another important effort began in the early 1970s at the National Center for Scientific Research in the field of computational neurosciences, mostly with Cuban-designed and Cubanmanufactured hardware [6]. Since then, after a heavy effort to build up human scientific potential, mostly with the influence and support of Eastern European countries, the problem of Cuba’s limited computing potential was overcome and Cuban scientists gained valuable experience with microcomputers in the 1980s. Limitations to high-tech development during the 1970s originated from the obsolescence of devices built in the former Soviet bloc and a strong dependence on components from the same market, which hindered Cuba’s national hardware production. Cuba was well-positioned to take advantage of the benefits of the microcomputer revolution of the 1980s. Applications of these new devices to the physical and biological sciences were frequent in that time and several computer programs were written or adapted to allow such applications [7,8]. During the economic crisis of the 1990s, these developments continued in the established groups and appeared in new teams at the Cuban Center for Genetic Engineering and Biotechnology (CIGB) [9].