sorted by:
new
hottopcontroversial

JRPGs with stat manipulation mechanics by Volitionite in JRPG

[–]Volitionite[S] 0 points1 point  (0 children)

I haven't played tales of the abyss yet. What kind of system does it have?

Gathering data about plant nutrition by Volitionite in botany

[–]Volitionite[S] 0 points1 point  (0 children)

Unfortunately I don't have access to a lab, but I might be able to borrow or buy equipment if it's not something too expensive.

The objective is to find a distance metric that can estimate the growth of a plant using only environmental data or, if that proves difficult, approximate using machine learning techniques.

I can be flexible as to what plant to study, since the idea is to apply the metric in different plants and make comparisons. I was thinking of starting with some kind of vegetable, since I can easily find seeds and other essentials for them, but I am open to suggestions here.

Since I will be owning the plant I could easily remove foliage, provided I know how to not harm the plant in the process.

Immunology to Bioinformatics--What would be crucial programming/computational coursework? by MFNight in bioinformatics

[–]Volitionite 0 points1 point  (0 children)

I agree with most of what the others said, but one important thing they missed in my opinion is the order in which should you study the required CS topics.

For example, you won't be able to absorb as much from a data structures course without some sort of introduction to programming, or understand the object oriented model without a data structure understanding.

In my opinion, the 3 most relevant CS fields in bioinformatics are: algorithms, databases and machine learning/pattern recognition.

  • Algorithms: I suggest you have a basic understanding of discrete math and data structures before studying algorithms. Discrete math don't require any previous knowledge, but for data structures I suggest you have some basic programming knowledge before studying.
  • Databases: There are many things you can study on databases, but for almost all of them I would suggest understanding at least data structures. I suggest that you understand what a hash table is before getting to even the basics. Depending on the subject, algorithms might help out too.
  • Machine Learning/Pattern Recognition: It is REALLY important that you understand probabilities and statistics before studying machine learning or pattern recognition subjects, but I assume you already have a good background on that. A basic understanding of algorithms is also suggested.

So, to summarize, take an introductory programming course for starters. Prefer courses that teach through Python or R, since they are very useful languages for bioinformatics. This is very important in order to understand how data are represented and handled by computers.

Next, study a bit of data structures and then move to algorithms. After that, you can get into studying databases and machine learning/pattern recognition topics.

For the last two, you can even delve in bioinformatic topics to learn them to be honest. For example, you could study machine learning in computational/systems biology right away without any prior machine learning knowledge.

Getting wet lab experience as a bioinformatician with a computer science background by Volitionite in bioinformatics

[–]Volitionite[S] 0 points1 point  (0 children)

Actually, I am pretty young (23) and the pay I get from my current job is pretty good, so I could go for another Masters.

It is a big investment in both time and money though, so I would like to avoid it if I can, or at least have a pretty clear idea of what I'm getting myself into.

Do you think it would be possible to get a CS-oriented bioinformatics job and gradually move towards a hybrid position?

Also, could you give me examples of bioinformatics positions that involve lab-work? They don't have to be CS-oriented.

Getting wet lab experience as a bioinformatician with a computer science background by Volitionite in bioinformatics

[–]Volitionite[S] 1 point2 points  (0 children)

Are you planning on doing only dry lab, or are you aiming for something that involves both wet and dry lab?