3. Data, Science & AI

Creates publication-quality phylogenetic tree visualizations with Biopython and Matplotlib, supporting custom styling and multi-format export.

Identifies topologically associating domains (TADs) in Hi-C genomic data using insulation scores and HiCExplorer, including boundary detection and hierarchical structure analysis.

Performs geometric analysis on protein structures including distances, angles, RMSD, and SASA using Biopython Bio.PDB.

Performs metagenome assembly from long reads using metaFlye and metaSPAdes, enabling reconstruction of microbial genomes and MAGs from complex samples.

Assesses genome assembly quality via QUAST (contiguity) and BUSCO (completeness) metrics for validation and assembler comparison.

Normalizes and transforms Hi-C contact matrices using cooler and cooltools, applying ICE correction and generating observed/expected matrices for genomic structure analysis.

Generates reverse complements and complements of DNA/RNA sequences for bioinformatics tasks like primer design and strand conversion.

Filters genomic alignments by flags, mapping quality, and regions using samtools and pysam for targeted read extraction and quality control.

Analyzes site localization, motif patterns, and quantitative PTM data for phosphorylation, acetylation, and ubiquitination in proteomics samples.

Analyzes restriction digest fragments using Biopython, predicting fragment sizes, sequences, and simulating gel electrophoresis patterns for DNA analysis.

Enables cross-referencing between NCBI databases (genes, proteins, sequences, publications) via Biopython Bio.Entrez for scientific data exploration.

Analyzes multi-modal single-cell data from CITE-seq, Multiome, and spatial techniques, integrating RNA, protein, and epigenetic modalities per cell.

Generates genome browser visualizations with multiple tracks (coverage, peaks, genes) for specific genomic loci using bioinformatics tools.

Finds restriction enzyme cut sites in DNA sequences using Biopython's Bio.Restriction module, supporting single enzymes, batches, and commercial sets for linear or circular DNA.

Performs manual and automated gating in flow cytometry to define cell populations using rectangular, polygon, and data-driven gates for hierarchical analysis.

Performs cell phenotyping in IMC data using manual gating, clustering, and automated classification based on protein marker expression.

Imports gene expression count matrices from multiple formats (CSV, TSV, featureCounts, Salmon, kallisto, 10X) for downstream bioinformatics analysis.

Statistical analysis of CRISPR screen data to identify essential and resistance genes using MAGeCK, BAGEL2, and drugZ for hit calling.

Designs custom CRISPR sgRNA libraries for genetic screens, including sgRNA selection, library composition, and control design for knockout, activation, or interference experiments.

Phases genotypes into haplotypes using Beagle or SHAPEIT for VCF file preparation in imputation, HLA typing, and population genetics.

Computes evolutionary distances and constructs phylogenetic trees from biological sequence alignments using Biopython's TreeConstruction module.

Polishes genome assemblies and calls variants from Oxford Nanopore sequencing data using neural network models.

Reads and parses biological sequence files (FASTA, FASTQ, GenBank) using Biopython's SeqIO for efficient bioinformatics data handling.

Transcribes DNA to RNA and translates RNA to protein sequences using Biopython, supporting ORF detection and codon table customization.