 Dear students, in this module I am going to talk about the frontiers in bioinformatics. Bioinformatics is a relatively new area and it is still developing. The pace of development in bioinformatics is quite fast. However, it does not mean that it does not have its share of challenges. There are a huge number of challenges in the development of bioinformatics and are primarily originated from either a lack of computational power that is we don't have powerful computers to simulate the biological data or the biological data itself is so complex that we cannot handle it. So based on these two fundamental issues there are several challenges that come in the way of bioinformatics. For instance, in genomics we have the next generation sequencing for the next generation genomics. The NGS experiments they churn out vast amount of data sets and to find genes by assembling the genome together is an extremely complex task. You can imagine the complexity by looking at the size of data that is output from such experiments. The data is actually in terabytes. Also once the data is so big you want some methods to handle this data. For instance, just to copy a file with one terabyte of size is an extremely difficult task. Just imagine how much time it will take to process and analyze that file as well. Also the genome assembly and prediction becomes difficult once you are even unable to handle the file properly. Obviously it becomes difficult to analyze the data that is there within such files. In case of transcriptomics at a level higher than genomics there are several challenges as well. For instance, several RNAs have been discovered. The types of RNA and the role they play within the biological life is extremely complex. Moreover, these RNAs have structures. So how do their structure and their sequence they play a part in the cell life? The RNAs are known to also interact with proteins. So how do their interaction vis-a-vis their structural interaction goes? How can we model them? Bioinformatics is very helpful in doing it but still there are lots of challenges that are lying in this field. Next higher than transcriptomics is the proteomics area or the protein science. In case of proteins, we would like to know which proteins exist within a sample from a patient so that we can evaluate those proteins towards their role in a disease. Also, once we know how much of some proteins exist within a sample then we would like to do it for the entire patient biopsy sample. This is called large-scale proteomics wherein you just take a sample from the patient and you analyze the entire set of proteins that are there within the sample. This is very crucial for studying diseases such as diabetes. Also, once you identify which proteins are there you still want to know which post-translational modifications are there on each of those proteins. So these challenges are computationally hard as well as biologically complex and they represent the frontier in bioinformatics. In conclusion, bioinformatics is full of opportunities as well as challenges. I am sure you will be up to them after you take this basic course. Next, there are several other frontiers that belong to the cell level. We're going to look at them in the next module and they include the protein structures, the systems biology as well as personalized medicine.