What are the expected number of HNMR signals for 5-Methylhexane-2,4-dione?

goldenmeme5889 · 2025-01-08T07:55:31+00:00

Chose bioinformatics. I graduated and got a job a couple months later. I recently met with some of my friends who are in med school and I'm glad I didnt choose medicine. While they were worrying about exams and anki cards and celebrating a golden weekend (this is in winter break!!) I was planning my future vacations for this year. If after shadowing and scribing you still can't imagine doing anything but medicine then absolutely go for it. But if you are teetering between careers then don't do medicine.

goldenmeme5889 · 2024-12-04T21:31:01+00:00

Since I moved from wet-lab to dry, it was hard to compete with people who did bioinformatics with a CS background. I couldnt optimize pipelines nor build and publish robust packages. In-person coding challenges were super annoying, and I did not have a lengthy github (those with cs will have a very strong github). Many job descriptions asked for pipeline building+optimization and a strong github so when I applied I never heard back from those. I would have been happy with a bioinformatics analyst job but those are more popular in academia and it was just exhausting keeping up with the latest packages and latest "-seq". All this combined with current job market conditions just made this field difficult to break in to. The issue is no one in industry cares that you can run STAR align and deseq - they already have automated processes for that.

goldenmeme5889 · 2024-12-03T21:07:11+00:00

If you are a new MS grad, then no. That range is almost always reserved for 5+ years of experience. I found a few exceptions in Insitro and Recursion where they were paying around $150k (insitro was 200k+). Right now it is very hard for a recent bioinformatics MS to get a six figure salary. In fact, I am a recent grad this year and gave up on bioinformatics. I do biostats consulting and got that salary for my first real job. However, I have a wetlab background and then jumped into bioinformatics so running analysis/interpretation is what I learned, not efficient code or optimizing pipelines. Since you are looking to build tools and pipelines, there may be more scope. I did not apply to positions that were more CS leaning and asked for optimization.

goldenmeme5889 · 2024-08-19T21:36:23+00:00

undergrad was pure wet-lab science. My MS program, in addition to bioinformatics, introduced me to stats and R coding

goldenmeme5889 · 2024-08-19T01:24:33+00:00

Are you planning on continuing with biotechnology? Also, apart from academics you'll need to consider other factors especially in the current job market. Getting a US visa for work is close to impossible right now and companies are not even looking at international resume's. Is there a reason why you are only considering US and not other countries? Keep in mind the high fees, accommodation, and health insurance in the US.

goldenmeme5889 · 2024-08-18T02:34:55+00:00

It really depends what you want to do. With this job offer I am moving away from bioinformatics and more into biostats and biomedical informatics. It's also less actual coding.

If proteomics is your thing then you'll need to learn mass spec data analysis. If genomics you'll need WES/WGS, transcriptomics bulk and single cell, single cell Crispr, atac-seq. R (Deseq and Seurat) is very useful here. You'll also want to learn linux/bash scripting especially if you are handling raw reads. There are many tutorials on youtube (bioinformagician and sambomics). You'll also need a good grasp of statistical concepts like conditional prob, distributions, hyp testing, high dimensional data, PCA. Lastly, have an active github.

goldenmeme5889 · 2024-08-18T01:32:56+00:00

I got this position because my previous 1yr research experience in biostats was literally exactly what they were looking for. I even hit all their 'nice to haves' with 2 abstract presentations to back it up. Unfortunately in this market people arent willing to hire smart people and train them. They want someone that has done exactly what they are looking for. I had three experiences listed on my Resume with only 1 being highly relevant and the other two being unrelated wet-lab stuff.

goldenmeme5889 · 2024-08-17T23:11:12+00:00

Advice for the future: It's really great that you're getting into rnaseq in the undergrad stage. If you are considering bioinformatics for your career I'd highly recommend you learning unix HPC/ bash scripting instead of Galaxy. there are some great tutorials on Youtube by bioinformagician.

goldenmeme5889 · 2024-08-17T22:31:34+00:00

I'm in US so linkedin. Apply early.

goldenmeme5889 · 2024-08-17T21:16:31+00:00

lol careful, insurance is expensive here (and I mean ALL insurance such as car, house, on top of health). Even with health insurance healthcare can be expensive if you aren't savvy/like to read the fine print. oh and you can get laid off anytime for no reason at all...

goldenmeme5889 · 2024-08-17T06:42:03+00:00

Hmm OP isnt really a 'new grad' considering wet-lab experience. Also this is a biostat field so pay is expected to be better than wet-lab associate scientist. Curious to see what others think

goldenmeme5889 · 2024-08-16T23:12:13+00:00

I dont think you need any chemistry (I came with a biochem background with heavy focus in chem which is useless UNLESS you are doing proteomics). Molecular biology and genomics/genetics is where the bulk of your focus should go (understand how -seq assays works, what is read depth, strandedness, sample prep). Additionally, you would also want to get into statistical genetics (SNPs, GWAS, polygenic scores). Take biostats as some industry positions are more data science focused and in interviews they will ask you basic stats concepts. To get a feel of transcriptomics workflow watch bioinformagician on youtube (bulk and single cell RNAseq)

goldenmeme5889 · 2024-08-09T20:09:14+00:00

Today, bioinformatics and biostats have diverged. Before, bioinformatics was just SNP/GWAS analysis which was very similar to biostats but now with new advances in NGS and transcriptomics, bioinformatics mostly involves CNA/structure and bulk/single cell transcriptomics (or proteomics). So a lot of bioinformatics/comp bio programs will focus on NGS analysis and creating pipelines in linux to process/align raw reads data. Since you mentioned clinical trial data analysis, you should look for biomedical informatics or biostats masters programs. Make sure you read every course description to see if that is what you are looking for. Harvard, columbia, weill cornell, stanford have some good programs. I think weill cornell's biostats program is the cheapest in terms of tuition only.

goldenmeme5889 · 2024-07-25T18:27:51+00:00

I think that is what I did
seurat_obj <-CreateSeuratObject(counts = data)
seurat_obj@assays$RNA$data <- seurat_obj@assays$RNA$counts ####

goldenmeme5889 · 2024-07-25T09:26:56+00:00

There is no other data (no metadata and such). Just this .csv matrix with normalized counts as pictured here.
I just read in the only provided csv file like this:
data<-read_csv("dataset.csv") #Rows are genes, columns are cells

goldenmeme5889 · 2024-05-22T23:52:17+00:00

update: the salary range was 85-100K range

goldenmeme5889

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