Computational Biology
Algorithmic and data-driven approaches to biological questions, with emphasis on reproducibility and biological interpretation.
Academic work spanning computational biology, bioinformatics, molecular evolution, molecular modelling and practical computational training at the Central University of Himachal Pradesh.
Research themes are presented separately from the teaching platform so Bioinfo Compass remains an educational resource rather than an institutional profile page.
Algorithmic and data-driven approaches to biological questions, with emphasis on reproducibility and biological interpretation.
Protein structure, ligand recognition, docking, molecular dynamics and computational analysis of biomolecular systems.
Molecular evolution, comparative genomics and phylogenetic approaches to biological history and function.
Teaching resources are organized around concepts, practicals, interpretation and independent challenges.
Sequence retrieval, BLAST, alignment, conserved regions and interpretation.
PDB literacy, docking controls, simulation workflows and trajectory interpretation.
Biological strings, FASTA, PDB parsing, file handling and reproducible analysis.
Learn what to use, why to use it, and how to interpret the result. A curated field guide and practical training environment for bioinformatics students.
Curated databases and tools. Filter by task, level and resource type; then move into Learn or Workflows when you want guided training.
Every lesson follows the same five-layer model: concept → method → practical → interpretation → challenge.
Start from a biological task rather than from a software name.
Short, inspectable examples designed for teaching. The PDB exercises deliberately begin without Biopython so the file format is understood before abstraction.
Use these after completing a learning path. They emphasize interpretation rather than button-clicking.
Concise definitions of terms that repeatedly appear in practical analysis.
A quiet corner of Bioinfo Compass for curiosity, persistence, scientific humility and the habits that make computational work meaningful.
Ideas worth carrying into the laboratory, classroom, or the next difficult problem.
Short scientific comics about mistakes, uncertainty, debugging, validation and discovery.
The page selects from a larger internal collection. Only the current thought and story are shown in the interface; selections do not auto-rotate while you are reading.