 These students in this module I am going to expand on the frontiers in bioinformatics. As you already know that the next generation sequencing transcriptomics and high throughput proteomics they present several challenges to us as bioinformaticians. However, these challenges are simply not the end of it. There are even more complex challenges in bioinformatics some of which I am going to elaborate on in this module. You know that the proteins are 3D objects. They are folded in their natural environment and they perform specific functions. But the problem is that we don't know the complete foundation that is there for folding a protein. This is one of the hardest problems in biology. Can we use bioinformatics to predict how these proteins are folding? It can be a very interesting idea. Several people are working on it already but it is a very hard problem in fact. Moreover, instead of predicting the structures of proteins can we go in the lab and experimentally find the structures? Yes we can. However there we have a very different kind of problem. All the proteins cannot be crystallized. All the proteins cannot behave in a way that allows us to find their structure. So there are these unique challenges that the protein structure throws at us and bioinformatics can be useful in dealing with them. Moreover, once a protein starts folding can we somehow simulate this process? It is also a very tough challenge. Bioinformatics is trying to cope up with this challenge but it is a very hard problem as well. Next, can we somehow predict how the two proteins will interact together once they come together in the cytosol? This is very important if you want to look at the protein-drug interaction. Therefore, this is also a very important challenge which bioinformatics is yet to handle. Next is the frontiers in systems biology. You know that in biology cells are the independent units and they have their own life and they behave according to their own phenotype. So if the cells they act on their own can we somehow model them and look at their system level properties. That is those properties which are given birth after several cells come together in a single simulation and you look at their overall property such as formation of a tumor in cancer. So how to integrate the genes, the proteins, the networks, the interaction between proteins within a cell if you want to create such a simulation? That is a very unique challenge in systems biology. Moreover, once you get a model how to simulate it in real time? How to simulate it fast enough to predict how the colony of cells will behave in let's say six months? You cannot possibly run a simulation for six months to see the results. So you would want to do it in a fast manner. Next are the frontiers in personalized medicine. You know that not all the medicines they work all the time. Some of the people also get side effects by taking specific medicines. So there must be a detailed study into how the drug behaves once it's taken up by a patient. Bioinformatics is trying to address this challenge as well. However, this is one of the very tough problems again. So how can we use bioinformatics to evaluate such interactions? It can be a very interesting problem for you as well. In conclusion, the 21st century is going to be the century of bioinformatics. Biology and life itself has vastly vast spans of misunderstood or totally not understood portions. And we want to understand those portions in light of high throughput data from genomics, proteomics, transcriptomics and other new areas in bioinformatics. We know that it will usher us into an era of personalized medicine where several of the diseases which we know will no longer exist.