Murali Jayapala

When we talk about biosystems or biodesign or anything related to the convergence of biology, electronics and computer science, it is important to understand the different categories that exist in this convergence.

  1. Bio-Electronics
  2. Computational Biology (Systems Biology)
  3. Biological Computation
  4. Journals
  5. Conferences

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In this category efforts include how to interface conventional electronics with biological entities (input/output boundaries). Here we build sensors and actuators (e.g. Microarrays) that can talk to the biological entities directly. Essentially, we take information from the biological entities, convert them into electronic signals, do some processing on the signals and then try to control the biological entities by controling the actuators.

Some useful links

Computational Biology

In this category efforts include using conventional computing paradigm to understand what is happening with biological systems. This broadly could be seen as applying knowledge of computer science and engineering into biological sciences (Comp sci -> Biology). In general this is also called as Systems Biology.

One sub-category is to come up with models for analysis of biological systems, based on the internal behaviour of the biological system. Essentially, abstract models of biological entities/systems are made using paradigms in comp sci (e.g. dynamical feedback control system from Systems theory) and run elaborate simulations to understand how the biosystems work.

Another sub-category is to analyze the data based on the external observed behaviour. E.g. is Bioinformatics. Bioinformatics is sometimes synonymously with computation biology. This sub-category includes the application of data management, data mining, data modeling and algorithmic techniques to biological databases, such as genome databases and related sequencing information. This category is closely related to computational biology, at least the goals are quite similar, except bioinformatics is more specialized to data management and data mining of biological information.

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Synthetic Biology

Closely related to the above general category is this category, the aim is to create new life forms or synthetic life forms. We know how to read the DNA of a biological entity. Can we create new DNAs and using this new DNA create new life forms? How to make such a design? Many design method principles used in conventional semiconductors could be applied in design of synthetic life forms. Note that in the most general form, both Computational Biology and Bio-Computation would be under synthetic biology. This field is the new pardigm for biological engineering.

Some useful links

Biological computation

Also check: Non-Standard Computation

In this category efforts include using knowledge and models of biological entities to enhance computer science and engineering. This broadly could be seen as applying knowledge of biological sciences to computer science and engineering (Biology -> Comp sci) in the form of generalized computing platforms. As we know such a platform has few crucial aspects: computing, storage, communication. (i/o is covered in the first category of Biochips)

One sub-category is related to computing. This include efforts to use biological entities as the basic building blocks to make conventional computers (instead of semiconductors). Our conventional computers are based on the Von Neumann model. There is a whole computing paradigm build around Von Neumann which is used to build the computers. Conventional computers are built using transistors (semiconductors). Instead of semiconductors, can we build computers using the biological entities instead? This is the essential question being addressed in this field.

Another sub-category related to computing, which is relatively new, include efforts to come up with new computing models. Von Neumann model has been very successful abstract machine. But how does biological entities perform computation? What is the model for biological and chemical processes? Can this model be used to perform computation, can this provide a new computing paradigm? Can we write "programs" using this new paradigm.

There are other sub-categories where biological models are used to come up with new and improved ways for storing information and as communication medium between different entities.

Some useful links


Interesting Conferences