Forum:Beginner: looking for suggestions

Question

[zeroonehacker]

Hi,

I am Dushyant, mathematics and computing student. I started to solve problems on Rosalind platform and it developed my interest in Bioinformatics. But, I have no clue how to start and what is the best path to do it. For starter, I am reading "Fundamentals concepts of Bioinformatics by Krane and Raymer". I only have school level biology knowledge and I don't know if it is sufficient but I can surely grasp the content of this book. Being a computer science student, I am good at programming so I want to learn more things to get better in Bioinformatics. Can anyone suggest me or point me to some post which shows a learning path suitable for my background. Thanks in advance.

[GenoMax]

Hi Dushyant: There are many past threads based on this topic (you should use google to do an external search on Biostars). Here is one: Beginner in Bioinformatics / computational biology field

[zeroonehacker]

Thanks for the reply and the link. I did a search but I wanted an experienced opinion from the member of the community that someone with my background followed and it helped.

Answer 1

[noorpratap.singh]

Being from a CS background my self, I can perhaps provides some insights. Bioinformatics as such is a vast field, covering different areas. Since programming wont be much of issue, biology and statistics background is something you need to pick up. Following two repositories provides a comprehensive list of resources

https://github.com/jtleek/genomicspapers

https://github.com/ossu/bioinformatics

[zeroonehacker]

Thanks for the answer. I am adding to my question: I have specialization in statistics and deep learning. Thanks for the link to the resources, I will definitely look into those :)

Answer 2

[WouterDeCoster]

In bioinformatics, all experience and knowledge of computer science, programming, deep learning and statistics is close to useless without a firm biological understanding of the data you are working with. Knowing biochemistry, genetics, transcriptomics or proteomics is necessary, depending on your field of interest.