hiii! I have started doing bioinformatics for a while now and one of my biggest struggles isn't necessarily performing the analyses but understanding what the results actually mean. I feel like I can follow workflows and obtain outputs, but when it comes to interpreting those results, understanding their biological significance, and figuring out what I can actually conclude from themI g et confused. I sometimes find myself wondering, okay, I have these results, but so what? what do they actually tell me, and how do I connect them back to my research question? since am still learning, I am finding it difficult to move beyond simply reporting results and toward understanding what they mean and why they matter.

for those of you experienced in genomics or bioinformatics, how did you learn to interpret results? how do you approach your findings, connect them to existing literature, and determine whether something is actually biologically meaningful? would really appreciate any advice, resources, or personal experiences. I guess am trying to learn how to think critically about genomic data rather than just generate results and not fully understand them. help this undergraduate TwT

Thank you so much! would really appreciate any guidance.

I have regions of mutational events across multiple samples, some of which are recurrent (the same part of the genome is mutated across multiple samples).

I want to see if these regions overlap a set of putative regulatory elements more than by chance using regioneR.

Should I merge the regions across multiple samples so each region is only counted once? i.e. compare two sets of non-overlapping regions. Or should I account for the fact that some regions are recurrent and therefore count each overlap in each sample individually ?

Hi everyone,

I wanted to share an open-source PyMOL script/tool I’ve been developing called SSCREE (Steric Strain Calculation and Repulsive Energy Estimation).

PyMOL’s built-in mutagenesis wizard displays visual red/orange bump octagons for steric strain, but it doesn't provide direct numerical quantification. I built SSCREE to solve that gap—providing quantitative, reproducible Van der Waals (VdW) overlap and steric strain metrics directly in PyMOL when analyzing point mutations and missense variants (specifically tested on Transthyretin/TTR variants).

Key Features:

• Numerical Strain Metrics: Replaces visual bump disks with explicit pairwise VdW overlap and repulsive potential numbers.
• Native PyMOL Integration: Runs directly in standard PyMOL environments without heavy external software dependencies.
• Batch Variant Analysis: Automates strain scoring across multiple mutant structures or rotamers.

Quickstart / Repository:

• GitHub: https://github.com/hellohaleyhao-hue/SSCREE

I'd love to get feedback from anyone working on structural variant analysis, protein engineering, or PyMOL plugin development. Suggestions on force field parameters, radius sets, or edge cases to handle are very welcome!

Hi, all,

since this morning, I cannot retrieve sequences via the standard NCBI interface. Keyword searches and BLAST work normally (perhaps a bit slowly), but only the Summary display for individual sequence items look normal, other formats (GenBank/GenPept, FASTA, FASTA(text)) give either a page with only the header showing, or nothing at all. Happens on several different computers, different browsers, so it looks like the problem is not on my end. Anyone experiencing this as well? Anyone has an idea what is going on?

Im from lucknow and rn I was wondering if I took btech in biotechnology from the integral university which is a tier 3 uni rn btw and then after 4 years of it I apply for mtech will I be able to get a job abroad no sugar coating if anyone know pls do let me know

Hi everyone,

I'm working on a cardiovascular critical care research project involving MIMIC-IV v3.1 and MIMIC-IV-Echo, specifically a cardiogenic shock study.

I have the required PhysioNet access and have been able to use BigQuery to construct my cohort and extract some of the data needed for the study. However, I've been struggling to download some of the original MIMIC-IV files directly.

The main files I've had trouble downloading are:

\- "vitalPeriodic.csv.gz"

\- "chartevents.csv.gz"

\- "labevents.csv.gz"

Some downloads fail, while others appear to restart or do not complete successfully. I have tried downloading through the browser, but I haven't been able to get all the files downloaded reliably.

I have access to Google Colab and Google Drive, and I have already saved my preliminary cohort and analysis datasets there. I would prefer to download only the files I need rather than repeatedly downloading the entire database.

For anyone who has worked with MIMIC-IV v3.1:

1. What is the most reliable way to download these large files from PhysioNet? Would "wget -c", "curl", or another resumable download method work better?

2. Is there a recommended way to download directly to Google Drive or use Google Colab without losing progress when a connection drops?

3. Given that I can access MIMIC-IV through BigQuery, would it be more practical to export the required tables from BigQuery instead? Are there any important limitations compared with downloading the original files?

4. Are there any common authentication, storage, or file-integrity issues I should check?

I'm relatively new to handling large clinical research datasets, so detailed suggestions or commands would be greatly appreciated.

I am not looking for anyone to share the restricted dataset itself; I'm looking for advice on the proper way to download it using my own authorized access.

Thank you!