I have a question where I don´t know how to start this. We did a scRNA sequencing experiment and I now have an AnnData dataset. I already know a lot about this dataset mainly by using scanpy library and I would like to "finalise" the analysis by extracting genes that have a specific RNA sequence in the 3'UTR.
Unfortunately I have no idea how to approach this since I am no bioinformatician and couldn´t find a tutorial to do this. Can someone please help me with this problem?
Here how it looks like.
Thanks in advance!
I just found a way around in R. It is on the bases on BSgenome.Mmusculus.UCSC.mm10. You can find the answer here. Just read in the result in python as a list and us the function sc.tl.score_genes to see where they are enriched.
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I am pretty new to coding and I'm currently stuck on the following practice questions in my textbook.
Write a program that generates an 'eight puzzle'. It should randomly shuffle the puzzle, then allow the user to solve it.
Extend your program so it has a 'solve' option that will solve it using A* search.
The problem is, after hours of browsing the web and YouTube, I only come across tutorials and examples which either assume advanced knowledge of this topic or include no useful annotations which would help me learn it.
I was wondering if anyone could please point me to a resource of some sort that explains how to even approach such a puzzle in Python 3. I have no clue what the best way to learn and start this is.
Thank you in advance for your time and help.
Can someone please help me in finding the regular expression for the given automata?
I know the basic steps of finding but in this question I'm stuck because in this case the initial and final states are same as well as their is a two parallel loops.
I tried it by applying basic rules for finding regular expression but after some steps I'm stuck. Please help me in solving this.
A new approach of finding would be appreciated.
Thanks!!
hope u fine
i applied "bypass/state elimination algorithm" on this DFA
after solving it out ..i retrive this RE maybe it looked some what like messy but yes you can check it out by testing different string .here it is
1*+ (1*0(1)*0(0)*1).((01*0+1).(1)*(0(0)*1))*.0
I'm doing some analysis on GitHub comments. But for that, I need to exclude the code samples and error messages from the comments automatically from a large set.
The other easier way to say this would be, I can keep only the English part of the comments. Although there are few libraries to detect the language of a sentence, there are few challenges in my case too. 1) the comment part does not always follow proper English grammar, 2) the code sample and error message mainly consist of English words too.
So what should be my best approach. The results don't need to be 100% accurate, I just want to know the best approach that can give me a satisfactory result at least. Any idea?
This question is old, but my Google search led me to this question; so offering this answer in case anyone stumbles into this question, too.
I'm trying to develop something that extract keywords from a text. I know AlchemyAPI work best for this. Now i wanna know what algorithms AlchemyAPI used so that i can implement code of it on my own. Does anyone has any idea about it. Please share it. Thanks in advance.
I have no idea what specific algorithms AlchemyAPI uses (I'm guessing it is on the extreme end of proprietary), but the Stanford NLP has a lot of information and code that may be useful:
http://www-nlp.stanford.edu/software/lex-parser.shtml
I am looking for a tool that can analyze the emotion of short texts. I searched for a week and I couldn't find a good one that is publicly available. The ideal tool is one that takes a short text as input and guesses the emotion. It is preferably a standalone application or library.
I don't need tools that is trained by texts. And although similar questions are asked before no satisfactory answers are got.
I searched the Internet and read some papers but I can't find a good tool I want. Currently I found SentiStrength, but the accuracy is not good. I am using emotional dictionaries right now. I felt that some syntax parsing may be necessary but it's too complex for me to build one. Furthermore, it's researched by some people and I don't want to reinvent the wheels. Does anyone know such publicly/research available software? I need a tool that doesn't need training before using.
Thanks in advance.
I think that you will not find a more accurate program than SentiStrength (or SoCal) for this task - other than machine learning methods in a specific narrow domain. If you have a lot (>1000) of hand-coded data for a specific domain then you might like to try a generic machine learning approach based on your data. If not, then I would stop looking for anything better ;)
Identifying entities and extracting precise information from short texts, let alone sentiment, is a very challenging problem specially with short text because of lack of context. Hovewer, there are few unsupervised approaches to extracting sentiments from texts mainly proposed by Turney (2000). Look at that and may be you can adopt the method of extracting sentiments based on adjectives in the short text for your use-case. It is hovewer important to note that this might require you to efficiently POSTag your short text accordingly.
Maybe EmoLib could be of help.