Protein sequencing
“A Beckman-Coulter Porton LF3000G protein sequencer.” - via Wikimedia Commons
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Protein sequencing
“A Beckman-Coulter Porton LF3000G protein sequencer.” - via Wikimedia Commons
writing a lab report on my analysis of my TAS2R38 PTC taste receptor genotype and the page limit is 7-12. a 6 1/2-page introduction section is toooootally reasonable, right? i mean how am i supposed to not talk about the evolution and population genetics???
also for those who are curious: my genotype is AAV/AVI!! soooo cool cause AAV is one of the rare haplotypes!!! and i classify my phenotype as a taster, but only barely: PTC tastes kinda weird, barely even bitter but absolutely detectable. so cool!!!!!!
What we can learn from scientific analysis of Renaissance recipes
Multispectral imaging, proteomics, historical texts yield new insights into 16th-century medical manuals.
What we can learn from scientific analysis of Renaissance recipes
Everything, Everywhere
Traditionally, proteins in cells have been analysed individually to determine their locations, interactions and functions. More recently, proteomics (large-scale study of proteins) has enabled scientists to gain inventories of the multitude of proteins produced in a cell at a given time, but without any spatial and functional information. And now there’s spatial proteomics. By isolating a large number of individual organelles and structures from within a given cell type and performing mass spectrometry to determine the particular proteins associated with them, researchers can determine the cellular locations and potential interaction partners of thousands of proteins at a given moment. The image shows the barely-known protein TMEM184 (white), for example, which was identified as a lysosome-associated protein by the latest spatial proteomics technique. Knowing the cellular locations and associations of TMEM184 and, simultaneously, thousands of other proteins provides both a global and incredibly detailed view of the cell all at once.
Written by Ruth Williams
Image from work by Marco Y. Hein, Duo Peng, Verina Todorova, Frank McCarthy, Kibeom Kim and Chad Liu, and colleagues
Chan Zuckerberg Biohub, San Francisco, CA, USA
Image originally published with no restrictions – Creative Commons Attribution 4.0 International (CC BY 4.0)
Research published in Cell, December 2024
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this one is for my 12 other homies out there who have been on both sides of this meme
Common uses of bioinformatics
💡Sequence analysis Analyzing DNA and protein sequences to identify genes, regulatory regions & mutations.
💡Gene expression Analyzing RNA expression data from experiments like microarrays or RNA-seq to understand gene regulation.
💡Phylogenetics Constructing evolutionary relationships between organisms based on genetic data and genomic comparisons.
💡Molecular modeling Predicting protein structure and docking drugs to proteins using computational modeling and simulation.
💡Databases & Data mining Developing databases like GenBank to store biological data and mining it to find patterns.
💡Genomics Studying entire genomes, including sequencing and assembling genomes as well as identifying genes and genomic variations.
Follow @everythingaboutbiotech for useful posts.
day 11 // 100dop++
src: coffee shop vibes
The fastest way to kill something special is to compare it to something else. Sometimes it's other people, sometimes it's imagined successful versions of me many years from now and I wonder how I can ever be her with where I am right now and if it's possible at all. But I can't compare their many years of experience to my one. It just wouldn't be fair.
journal and/or meditate ✅ (been feeling anxious about lab stuff and rather annoyed in general, probs bc of not being entirely well rested, so i needed to meditate, i guess, even if it was hard.)
physio ✅
finish watching video on ms-based proteomics ✅
try to read 2nd package article ✅ (barely understood...gotta come back to it later)
slowly work through documentation of 1st package ✅ (still got a long way to go)
I hope the lab will still want me after they find out how little I actually know 🥺 But if not, it's back to studying at my own pace, which isn't that bad either. If I've learned anything in the past 2 days, it's that I really need to brush up on and learn more stats and math and how R plays a role in it, so that's what I'll be focusing on next if I don't get this position...
sample protein secondary structure features (labeled), made of folded cardboard ribbon
in theory, i Do have work to be doing, but in case it wasnt already abundantly clear, this work is not getting done 😔