BIOINFORMATICS WORKSPACES FOR GENOMIC R&D

Move genomic data into research decisions.

GenomeMiner gives microbial and genomic discovery teams one place to organize research data, run managed bioinformatics pipelines, follow analysis progress, and review results with collaborators.

Request pilot access Explore pipeline coverage

Free pilot access and project-based pipeline credits available.

Strain Discovery

Research workspace · 12 genomes

RESEARCH DATA

isolate_04.fastq

2.4 GB · tagged

reference.gbk

annotated

ACTIVE ANALYSIS

Flye Assembly

running · step 3 of 5

live

OUTPUTS

Prokka

annotation.gff

BUSCO

98.1% complete

Selected partners

Keep the research connected

Your science should not disappear into files, scripts, and handoffs.

Genomic research becomes difficult to follow when data lives in storage, analysis runs somewhere else, and results are shared through disconnected folders and messages. The analysis may be complete, but its inputs, history, outputs, and decisions quickly lose their context.

Fragmented research

Research files Analysis scripts Compute environment Run status Output folders Collaborator updates

GenomeMiner Workspace

Collaborators

Datastore

Pipeline run

Result

Output files

Logs

Analysis

Workspace activity · team notified when results are ready

Know what happened

Preserve the inputs, execution details, logs, status, and outputs behind each analysis.

Keep data and results connected

Manage research files and analysis outputs in the workspace where the project is being conducted.

Move work across the team

Give scientists, computational specialists, collaborators, and clients appropriate visibility into the same research program.

GenomeMiner creates a shared operational layer around genomic analysis so the work is easier to run, review, and continue.

One connected research loop

From research data to reviewable outputs.

GenomeMiner connects the practical stages around genomic analysis, keeping the data, execution history, and results available within the same research workspace.

Select a stage to update the preview

app.genomeminer.ai · Strain Discovery

GenomeMiner Datastore showing folders, research files, selected items, and the Actions menu

Every stage remains connected to the workspace, the initiating researcher, and the history of the project.

Pipeline coverage

Support for the work between sequencing data and biological insight.

GenomeMiner provides runnable pipelines across core genomic research tasks, from preparing sequencing data to assembling, annotating, comparing, and characterizing genomes.

Illumina Read Processing Nanopore Read Processing Dorado Basecaller Dorado Aligner Minimap2 NanoPlot

Canu Flye Hifiasm Hybrid Assemble Unicycler BUSCO Merqury

Prokka MiGA Taxonomy MetaPhlAn 4 BGC Identification AMRFinderPlus PlasmidFinder geNomad

Nanopore Variant Calling VCF Sample Diff Plotsr GSEApyEnricher RNA Aging ElasticNet SoilMicrobiomeDroughtML

Discuss your pipeline needs

One workspace, appropriate visibility

Keep scientists, computational specialists, and external partners aligned.

Research programs involve people with different responsibilities. GenomeMiner lets teams organize their work in shared workspaces while controlling who can manage the project, contribute to it, or review its results.

Owners and editors

Manage the workspace, organize data, configure pipelines, and guide the research program.

Manage & run

Collaborators

Work with shared project data, follow activity, and contribute to the research process.

Contribute & review

Clients and external partners

Access a restricted, results-oriented view of the relevant workspace.

Follow results

Workspace activity, runs, members, research files, and resource use give project leads a clear view of the program.

Fit the platform to the program

Start with the core workspace. Extend it when the research requires more.

GenomeMiner's core experience connects research data, managed pipelines, run history, outputs, and collaboration. Specialist capabilities can be enabled based on the needs of the workspace or account.

Core platform

Organize research data, configure pipelines, track analyses, review outputs, and collaborate within workspace-scoped projects.

Research data & datastore

Organize files, folders, tags, and archives in a structured workspace datastore.

Managed pipelines

Configure supported analyses with structured inputs, references, and parameters.

Run history & outputs

Track status, inspect logs, and retain outputs with their complete analysis history.

Workspace collaboration

Give teammates and partners appropriate access to project data, activity, and results.

OPTIONAL

Specialist tools

Extend selected workspaces with sequence editing, genome visualization, BLAST search, or cloud notebook environments.

Sequence Editor

Edit DNA/protein sequences, manage annotations, find ORFs, align, and work with GenBank annotations.

Genome Viewer

Explore genome data using FASTA, GFF, and VCF inputs.

BLAST Search

Create workspace databases, run similarity searches, and inspect or download results.

Jupyter Notebooks

Launch workspace-connected notebooks with configurable compute resources.

Pipeline & program support

If your team already has analysis processes, scripts, or deployment requirements, talk with GenomeMiner about pipeline design, migration, and the appropriate program setup.

Pipeline design & migration

Program & account setup

Deployment requirements

Discuss your research program

Example research programs

Three ways teams can apply GenomeMiner.

Program type

Microbial candidate discovery

Agbiotech & industrial biotech R&D

Microbial inhibition screening plate comparing Act17, Strep1, Strep2, and Bac — Microbial inhibition screening plate

Research challenge

A discovery team has promising isolates, but sample metadata, sequencing files, assemblies, and screening notes are split across tools. Comparing the evidence across strains makes it difficult to decide what to test next.

GenomeMiner setup

The team organizes each strain in a shared workspace, processes the reads, evaluates assembled genomes, and runs taxonomic, annotation, and biosynthetic gene cluster pipelines. Structured records connect candidates to their files, runs, and outputs.

Operational result

Researchers can review a traceable evidence package for each strain and prioritize the most promising candidates for wet-lab validation while retaining the full analysis history for collaborators.

Move from a library of isolates to a defensible experimental shortlist.

Program type

Production Scale Processing

Sequencing labs & bioinformatics teams

Sequencing quality summary showing per-base quality, adapter content, assembly contig lengths, and coverage depth distribution — Sequencing quality and coverage summary

Research challenge

New sequencing batches arrive regularly, but processing depends on scripts, local compute environments, and manually organized output folders. Status and quality decisions become difficult to review consistently across samples.

GenomeMiner setup

Illumina or Nanopore data enters a workspace and moves through managed read processing, assembly, and assessment pipelines such as BUSCO or Merqury. Run status, logs, parameters, and outputs remain attached to each analysis.

Operational result

Each sample follows a consistent, reviewable route from raw reads to an evaluated genome. Teams can inspect failures, rerun analyses, compare QC outputs, and retain approved results without reconstructing the process.

Make every genome reviewable, reproducible, and ready for the next analysis.

Program type

Custom omics pipeline

Translational & research-service teams

GenomeMiner pipeline selection showing private custom pipelines including EDMSeq, ekei.Align, and ekei.DNAm — Custom pipeline selection

Research challenge

A validated transcriptomics, variant-analysis, or machine-learning process still depends on a specialist to prepare inputs, run each step, and package results. That dependency slows repeat work and creates extra handoffs with collaborators.

GenomeMiner setup

The existing process is converted into a managed pipeline with structured inputs and known compute requirements. Workspace roles give researchers, computational specialists, and external partners appropriate access to data, run history, and results.

Operational result

The pipeline can be run repeatedly without rebuilding its environment or instructions. Specialists retain visibility into execution details while the wider project team can follow progress and review outputs in one place.

Turn a specialist analysis into a repeatable service for the wider research team.

Free project pilot

Try GenomeMiner with your own research project.

Discuss your project with us and we'll provide free platform access and pipeline credits matched to your data and analysis needs.

1Tell us about your data and research goal.

2We'll identify relevant pipelines and an appropriate credit allocation.

3You'll receive free platform access to evaluate GenomeMiner with your project.

Request free pilot access