Forum: Hot research areas in Bioinformatics for career development
gravatar for Pappu
4.1 years ago by
Pappu1.9k wrote:

From a senior postdoc point of view, it seems hard to raise funding or get tenure track position working on old research topics in which his/her mentor made career long ago. As such, I am wondering in which research areas should a postdoc focus from career development point of view. The following areas seems to be hot now a days:

Algorithm/web server development and data analysis for -

  1. Epigenomics (BS-Seq, CHIP-Seq etc)
  2. Metagenomics
  3. Genome Editing
  4. Non-coding RNAs
  5. Applications of Machine Learning (i.e. Deep Learning) in these areas
  6. Genomic Big Data Management



forum bioinformatics • 2.5k views
ADD COMMENTlink modified 4.1 years ago by Vivek2.3k • written 4.1 years ago by Pappu1.9k

Personally, I think the metagenomics is potential in many fields and I recommend the metagenomic sequencing in the study of microbial function in human health.

ADD REPLYlink modified 13 days ago by RamRS25k • written 4.1 years ago by sherrycd52510

The metagenomics area in interesting indeed. And there's also the holy grail of protein structure prediction, a field that hasn't progressed much since the 1990s, with the development of SWISS-MODEL and related programs (although I'd say that the problem's being confronted since the 1970s, when Chou and Fasman formulated their famous amino acid helix/beta sheet propensity tables).

ADD REPLYlink modified 4.1 years ago • written 4.1 years ago by Israel Barrantes750

I would include high throughput in-vivo imaging to the list.

ADD REPLYlink written 4.1 years ago by Alternative240
gravatar for Jean-Karim Heriche
4.1 years ago by
EMBL Heidelberg, Germany
Jean-Karim Heriche21k wrote:

This would depend on your career goals. If you aspire to lead your own lab, the most important is to find a good biological question/scientific problem to work on, i.e. a project with a clear direction that you can take with you to start your own group. If your goal is to latter sell your computational skills (within or outside academia) then you need to invest in learning skills that will be in demand where you want to go. But even so, at least in research, I think asking the right scientific question beats having a buzzword label e.g. indiscriminate application of machine learning to any and all biological question is not going to take you very far. If you can't figure out a new research direction, you're probably not ready yet to lead a lab.
If you're considering doing a postdoc, be aware of what you're getting into. I would advise to only do a postdoc in academia if you want to stay in academia despite the low pay and the long odds of getting some sort of stable position. See the report from the US National Academies on the subject and some articles on the topic here and here.

ADD COMMENTlink written 4.1 years ago by Jean-Karim Heriche21k
gravatar for vassialk
4.1 years ago by
vassialk190 wrote:

It depends on fortune, your relatives, your supervisors, your scores, publications, money and time investments. Genomics never will be natural, horrific and accurate as postmortem pathology. If you need topics, I can advise whole genome sequencing of microbes related to cancer and mononuclear microarrays of extreme conditions.

ADD COMMENTlink modified 13 days ago by RamRS25k • written 4.1 years ago by vassialk190
gravatar for Vivek
4.1 years ago by
Vivek2.3k wrote:

eQTL analysis, Allele Specific expression and in general anything linking variant calling with expression changes to show a causality. Following the recent trend of papers and having interviewed for a couple of jobs, those seem to be the popular, unsolved problems right now.

ADD COMMENTlink written 4.1 years ago by Vivek2.3k
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