Thanks a lot for the feedback, glad it helped! Feel free to share the lectures / channel with your classmates

My pleasure, I hope it was useful to you. Thanks for leaving a comment

It's my pleasure, thanks for taking the time to leave a comment.

Thanks for the concerns, nothing happened. Just been increasingly busy with my work as head of education at Applied Sciences, teaching, grants, and research. I just haven't been able to find much time to prepare new videos/livestreams. Ps. The steam release of Dwarf Fortress has also been a big time sink during the weekends.

@DannyArends Thànks for replying

Thanks for the kind words, the lectures and assignments are on KZbin, due to me having to teach online during COVID. I don't provide certificates, since the lectures are part of the MSc biology program at the HU Berlin.

Of course you can choose any editor that suits you. My advice is just to use Notepad++, since I've tried a lot of different editors and on Windows I always come back to it. It's the ability to open huge text files, low cpu&memory usage, plugin systems, as well as multi-line editing is something that I haven't found in any other editor.

@@DannyArends sure, thanking u a lot for the response sir

It's a course for beginners / people with minimal experience in R

Thanks for letting me know, I'll reboot it once I'm back behind a PC (~1 hour from this message)

Thanks for letting me know, I'll reboot it once I'm back behind a PC (~1 hour from this message)

@@DannyArends thankyou sir, it back online !

Excellent, keep it up

Thanks for the kind words, and leaving a comment. The lecture about PCR amplification is called: "Primer Design for RNA/DNA amplification"

Yeah, I don't mind people using Rstudio when they know what they're doing there is no issue. However for beginners imho it's better to have a clear separation between code, interpreter, and data. I've used many different editors in the past, but for windows I always come back to Notepad++

Enjoy ! R programming is a very useful skill

Hi, thanks, glad you enjoyed the lecture series, I hope you'll enjoy the R lectures as well.

My pleasure!

Politics & Science are heavily intertwined

My pleasure! R packages are a great way to get your research out there

You're welcome, hope it was useful

Hi, there is no hard limit on the lectures. The original series was done for MSc and PhD students, but if you're interested, you can follow them without much prior knowledge and any unfamiliar concepts are easily googled. Enjoy the lectures and Python is a good choice for bioinformatics

@@DannyArends thank you professor...looking forward to complete the course

You're very welcome, hope you're enjoying the lectures

My pleasure!

Thanks, and yes I'm a big fan of free and open education and software. I can code all day and write one tool, but if I teach others, we'll have the many tools we need much faster.

You're welcome 🤗

Sure, just drop me an email and I can see how I can help you out.

Yep, it's just labels being put on things. For all fields (neuroinformatics & computational neuro) you just need to code and be an expert in neuro biology. General bioinformatics will give you a basis in both fields (coding & biology), after which you can specialize yourself more into the neurobiology field.

The main differences: PAM is based on global alignments of closely related proteins. BLOSUM is based on local alignments. BLOSUM matrices are based on observed substitutions from local alignments in the Blocks database, in contrast PAM1 is based on observed data of global alignments of closely related proteins, but all higher PAM matrices are extrapolated. Next, is that the numerical coding is inverted, a higher BLOSUM number means the substitution matrix is made by including more related protein sequences (more related), for PAM higher numbers mean more evolutionary time has occured for sequences to diverge (less related). The way I think about it, if you want to score a human protein versus a chimp use high BLOSUM or a low PAM. A human against a spider low BLOSUM or a high PAM. The following article which goes into great detail in how both PAM and BLOSUM matrices are computed: cs.rice.edu/~ogilvie/comp571/pam-vs-blosum/ Hope this helps.

I always advise people to pick up the "introductory statistics with R" book. It's a great resource for learning statistics and gives good examples that you can directly play around with in R

@@DannyArends Will do, Thanks!

Yes and no, in general introns are under less selective pressure than the coding regions of proteins (CDS), but are under more selective pressure than intergenic regions. However, this last part depends on the type of intron and splicing mechanism relative to what the function of the intergenic region is. In short most DNA is under selective pressure, the strength of this selection is very variable, e.g. the wobble bases in the CDS feel much less pressure than the first two bases of a codon. Selective pressure is furthermore heavily influenced by which protein you look at (and the environment), a ribosomal protein feels much more selective pressure than a pigmentation gene.

@ Thank you for the insight! Appreciate the response Professor

My guess is that most of the algorithms will be already available in R: Ishikawa diagrams, are provided by the qcc library (they're called cause.and.effect plots) The other 3 algorithms are harder to search for on google, since to me it is unclear to which area of research they are used in.

Much appreciated! I think it's a cool method

You are welcome!

Glad you enjoyed it!