(Part 2) Top products from r/labrats

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We found 21 product mentions on r/labrats. We ranked the 119 resulting products by number of redditors who mentioned them. Here are the products ranked 21-40. You can also go back to the previous section.

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Top comments that mention products on r/labrats:

u/McQueeny · 3 pointsr/labrats

I don't think this is exactly what you're looking for, but At The Bench - A Laboratory Navigator has a 10-page chapter about keeping a lab notebook.

Here's a brief Google Books preview; unfortunately it does not cover the relevant chapter.

This presentation(PDF link) cites a book called Writing the Laboratory Notebook by Howard Kanare, which (based on the Amazon reviews) might be more geared towards industry labs but could still be pretty useful in a general sense. You can find out for yourself, since I managed to find a full text copy online(PDF link). I don't think I'm accessing this through any proxies, so it does seem like it's freely available.

For a more thorough investigation of what's out there, you should consult your institution's library; I'm sure someone will be happy to help track down the exact book you are thinking of, or something functionally equivalent.

edit - here's a PDF link to another presentation, just for fun

u/virologyrl · 1 pointr/labrats

I have experience with MEGA to generate trees. I agree that it's a clunky software, but once you understand how to use it, it's not so bad.

I recommend the following book if you want to become a MEGA power-user: https://www.amazon.com/Phylogenetic-Trees-Made-Easy-Manual/dp/0878936068


Before you start... you say you are looking at the protein sequences. Are you starting with the amino acid sequence or the mRNA sequence? If mRNA, make sure all sequences are in the same orientation (ATG/start on the 5' end of the sequence). I find that if you have just one or two sequences that have been copied in the reverse direction, the alignment may not work. You can also save multiple alignments -- try some with seemingly more conserved sequences (less gaps) and try the entire set.

Once you have all your sequences in one FASTA file or multiple FASTA files, import them into MEGA. From the 'Align' menu, choose to edit/build an alignment. Add your sequences. Select all sequences for alignment and then align selected (you can get into some advanced settings here, change the alignment algorithm, etc.) Save the alignment as a .mas file and export as a .meg file.

Now, open your .meg file in MEGA's main window. From the phylogeny menu, select to build a neighbor joining tree. Based on the alignment, the program will auto-build a tree for you. Again, lots of functionality exists in the program, but it's not an intuitive UI.

Happy to help if you have other questions!

u/wormified · 2 pointsr/labrats

Might I recommend the late Jim Pawley's excellent and comprehensive Handbook of Biological Confocal Microscopy?

Handbook of Biological Confocal Microscopy https://www.amazon.com/dp/038725921X/ref=cm_sw_r_cp_apa_i_odTYCbAS6N4TN

The Nikon microscopy U sites are good basic primers. I would also recommend getting to know the staff at your friendly local core facility who can help guide you on specific questions.

u/TheToiletDuck · 7 pointsr/labrats

Good for you!

Here are some beginner tutorials written by students at my work
https://ourcodingclub.github.io/tutorials/

Also this book is excellent!

https://www.amazon.co.uk/Getting-Started-R-Introduction-Biologists/dp/0199601623

Try to learn ggplot2, it's easier than the standard graphics

ANOVA is built into R but I you'll need to run an ANOVA on a linear or generalised linear model. It's covered in the tutorials I linked.

For example (this won't run it's just an example of code)

Model1 = lm(height ~ sex, data = datafile)

Null.model = lm(height ~ 1, data = datafile)

Model.test = anova(Model1, Null.model, test = "Chisq")

Summary(Model.test)



For a graph it depends on how your data is laid out but you could feed it raw data and plot the means with error bars in ggplot2 with stat_summary like so

ggplot(data = datafile, aes(x=sex, y=height, colour=sex))+

stat_summary(geom="bar", fun.y=mean, position=position_dodge(width=0.95))+

stat_summary(fun.data=mean_se,position=position_dodge(0.95),geom="errorbar")

Hope that helps.


Don't be put off, learning r will make future stuff so much easier. I barely touch excel now

u/stirwise · 1 pointr/labrats

El-P is always a favorite of mine, can't go wrong with Run the Jewels and Cancer 4 Cure is excellent, too. DJ Shadow's first album would also go well with your drug theme.
Outside the modern hip hop universe, I'd also recommend Funkadelic's Maggot Brain and Parliament's Mothership Connection.

u/reggietheporpoise · 2 pointsr/labrats

the song of the dodo by david quammen. one of my favorite science books. i wish there was an audiobook available, i’d love to experience it again on my commute to work.

u/AdditionalKangaroo · 3 pointsr/labrats

There are a few ways to do this depending on your model organism and preparation.

You can inject a viral vector with a cell type specific promoter driving the expression of a fluorescent protein in a live animal. Depending on the vector used, you wait a few days to a week and then sacrifice the animal. You can then use classic immunohistochemical techniques to detect the gfp or whatever fluorescent protein you used. You could also just use immunohistochemistry with a cell type specific antibody to begin with. Then you’d most likely want to take confocal images and use 3D reconstruction software. If your question involves more intracellular structures rather than general morphology, you’d want to process the tissue for electron microscopy. It would allow you to look at synapses, dendritic terminals, etc.

Caveats to always remember are the sensitivity and specificity of the antibodies you’re using.

If you have a slice preparation, you can fill individual cells with something like Lucifer yellow to see the whole shape and morphology - don’t think you can also select for specific cell type with that though.

If you’re interested in learning more about techniques, I highly recommend this book: https://www.amazon.com/gp/aw/d/0128005114/ref=dp_ob_neva_mobile

u/fireball_73 · 26 pointsr/labrats

Everyone needs to read 'The Immortal Life of Henrietta Lacks' - hands down the best science book I've ever read. The audiobook is good too.

u/ennervated_scientist · 2 pointsr/labrats

The analysis of biological data is fantastic for foundation stuff. Really recommend it.

https://www.amazon.com/Analysis-Biological-Data-Michael-Whitlock/dp/0981519407

u/TheCrimsonFrenzy · 1 pointr/labrats

http://kirschner.med.harvard.edu/files/protocols/Novagen_petsystem.pdf
pet plasmids manual from novagen. Some protein work scattered about, a lot of cloning. Mostly just generic stuff but can bring up ideas to consider.
https://www.sigmaaldrich.com/content/dam/sigma-aldrich/docs/Sigma-Aldrich/General_Information/1/ge-strategies-for-protein-purification.pdf No protocols but general information on purifications in general.
https://www.amazon.com/Principles-Techniques-Biochemistry-Molecular-Biology/dp/0521731674 Same. Some useful tips and explains care of equipment and uses.

u/ShesQuackers · 17 pointsr/labrats

Bad Science by Ben Goldacre is the only science book I've convinced my non-scientist family to read. It drastically cut down on the number of phone calls I get about whether or not some Facebook-promoted scam is going to cure whatever ails them.

u/Chrome7 · 2 pointsr/labrats

Generally papers are just submitted as a word document - the look and feel of the paper/layout is done by the journal itself.
If you're looking for a guide on how WRITE a paper in the scientific language of a nature paper I recommend:
https://www.amazon.com/Essentials-Writing-Biomedical-Research-Papers/dp/0071345442

u/Level9TraumaCenter · 4 pointsr/labrats

Exactly what I was going to recommend. Fantastic book.

u/interlukin · 2 pointsr/labrats

We use these tackle boxes and haven't had any issues. We use 3-4mL of liquid to cover a membrane.