A cloud-based platform that lets researchers run large-scale genomic sequence alignments in parallel using the official NCBI BLAST+ toolkit. It handles batch uploads of up to 100 sequence files at once, adds AI-assisted result reporting, and presents species matches through clear, interactive charts.

The Automated BLAST Pipeline is an interactive Bash 4+ script that simplifies local NCBI BLAST+ workflows on Ubuntu by eliminating the need to memorize complex command-line arguments. You run the script, and it guides you through a menu-driven process that automatically handles dependency installation, detects nucleotide or protein sequence types, and restricts your options to only valid BLAST programs. To maximize compute efficiency, the pipeline fingerprints source FASTA files to reuse existing databases, utilizes all available CPU cores, and performs the search exactly once to generate multiple formats, including sortable HTML reports and data-ready TSV files.

A web app that rewrites dense scientific abstracts into plain language at three reading levels, built to solve a problem I hit weekly as a biotechnology student: most of the time spent on a paper goes into decoding vocabulary, not understanding science. Beginner removes technical terms entirely and explains through an analogy; Student keeps them and defines each one; Advanced preserves all terminology and statistics, simplifying only structure. Runs inference-only on NVIDIA's open Nemotron model via their hosted API, with responses streaming live. The system prompt is built explicitly against fabrication - the model may use only the pasted text, and refuses rather than invents when input is too thin.

An open-source, interactive pipeline that takes bulk RNA-seq data from raw reads (NCBI SRA, GEO, ENA or local FASTQ files) to differentially expressed genes, publication-ready plots and a fully verified HTML report – without the user writing any code. • 17 steps driving 15+ established tools: FastQC, MultiQC, fastp, HISAT2, samtools, RSeQC, StringTie2, featureCounts and R/DESeq2. • Every step verifies its own results: read numbers are reconciled from FASTQ to alignment to gene counts, and DESeq2 results are recomputed independently in Python. • Scientific decisions (trimming, library strandedness, experimental design) are explained in plain language and confirmed by the user – never guessed. • Checkpoints make long analyses resumable; changing a setting re-runs exactly the affected steps. • A reproducibility manifest records software versions, settings, file fingerprints and reference checksums. • Validated on synthetic truth data and real Arabidopsis and human (GRCh38) datasets; 274 automated tests and an 11-job continuous-integration suite. • Published on PyPI (pip install bulk-rnaseq-pipeline); Bioconda recipe submitted. • Comes with a 50-page illustrated User Guide and Learning Book for researchers without programming experience.