K-Dense Skills

Molecular biology toolkit: sequence manipulation, FASTA, GenBank and PDB parsing, phylogenetics and NCBI access.

Searches OpenAlex, PubMed and Google Scholar for papers, validates citations and generates BibTeX entries.

Designs experiments and studies before data collection: choice of design, randomisation, blocking and treatment layout.

Runs exploratory analysis on scientific data files: profiles, missing-data audits and outlier checks.

Turns observations into testable scientific hypotheses with rival explanations, predictions and an analysis plan.

Creates research posters in LaTeX with beamerposter, tikzposter or baposter.

Conducts systematic literature reviews across PubMed, arXiv, bioRxiv, Semantic Scholar and other academic databases.

Builds market research reports with traceable evidence, competitive landscapes and TAM, SAM and SOM sizing.

Converts Office files, PDFs and other documents to Markdown with Microsoft MarkItDown, for analysis and RAG ingestion.

Reference for Matplotlib: fine-grained control over plot elements and export to PNG, PDF or SVG for publication.

Creates, analyses and visualises networks and graphs in Python with NetworkX.

Prepares constructive peer-review drafts and structured assessments of scientific manuscripts and proposals.

Reference for Polars, the Python DataFrame library: expressions, lazy queries, streaming and migration from pandas.

Builds Bayesian models with PyMC: hierarchical models, MCMC, variational inference and model comparison.

Cheminformatics with RDKit: SMILES parsing, molecular descriptors, fingerprints, substructure search and reactions.

Writes research proposals for NSF, NIH, DOE and DARPA, with agency-specific formatting, review criteria and budgets.

Gathers current scholarly evidence, references and competing findings for a manuscript or research brief.

Runs the standard single-cell RNA-seq pipeline with Scanpy: QC, normalisation, clustering and differential expression.

Evaluates scientific claims and evidence quality: experimental validity, biases, confounders and evidence grading.

Builds slide decks for research talks, conference presentations and thesis defences.

Creates and audits publication-ready scientific figures with Matplotlib, Seaborn or Plotly.

Drafts, revises and audits scientific manuscripts with evidence provenance and reporting-guideline coverage.

Machine learning in Python with scikit-learn: classification, regression, clustering, model evaluation and tuning.

Statistical visualisation with Seaborn: distributions, relationships and categorical comparisons.