Author: BioCode Team

Why tumour purity and subclonality make depth decisive, what only WGS can detect, where panels win, and the matched-normal decision that matters more than any of it.

The three metrics that decide whether an ATAC-Seq library is usable, how to read the fragment size distribution, and how to diagnose exactly which step of the protocol failed.

Choosing clustering resolution, triangulating annotation evidence, spotting doublets and ambient RNA, and the replicate error that invalidates most single-cell differential expression.

Stabilising an enzyme, changing its specificity, and designing catalysis from scratch are three different problems with very different odds. What computation contributes to each.

Protein language models and text LLMs do very different jobs. Where embeddings genuinely outperform, where generation fails, and the evaluation error that inflates most published results.

How modern de novo protein design works, the real success rates, where it beats antibodies, and the filters that decide whether a campaign succeeds.

What each method actually measures, the biases built into both, what they cost, and a straightforward rule for deciding which your project needs.

From pathogen genome to a codon-optimised multi-epitope construct — the full immunoinformatics pipeline, and an honest account of which steps you can trust.

What MD simulation actually computes, what it is genuinely good for, the three ways it misleads people, and what you need to run one properly.

The five analyses that turn a molecular dynamics trajectory into a defensible result — what each measures, typical values, and how to tell signal from noise.