Where Biological Data Means More to
Discovery demands data, but raw biological data is chaotic. We bring structure to complex genomics, atomistic simulations, and multi-omics pipelines, turning petabytes of molecular code into confident therapeutic decisions.
Our Scientific Offerings & Analytics Solutions
Comprehensive data science, computational biology, and cheminformatics services designed to accelerate your R&D pipeline from target discovery to lead optimization.
Bioinformatics & Omics Analytics
Transform raw sequencing data into therapeutic breakthroughs. Comprehensive bulk and single-cell RNA-seq (10x Genomics), spatial transcriptomics, whole-genome and exome variant calling, and GSEA pathway enrichment.
- Single-Cell & Spatial Transcriptomics
- Differential Expression & Pathway Analysis
- WGS/WES Variant Annotation & Filtering
- Batch Correction & Cross-Cohort Harmonization
Computational Biology & Target Discovery
Deconvolve complex disease biology to identify high-confidence therapeutic targets. We integrate gene regulatory networks, CRISPR knockout screens, cell-cell interaction maps, and subclonal evolutionary trajectories.
- Target Identification & Prioritization
- Mechanism-of-Action (MoA) Deconvolution
- Cell-Cell Communication (CellChat)
- Clonal Evolution & Resistance Mapping
Cheminformatics & In Silico Screening
Accelerate hit-to-lead campaigns through high-throughput virtual screening, ensemble docking across 500,000+ compounds, machine learning QSAR modeling, and multi-parameter ADMET optimization.
- High-Throughput Virtual Screening
- AutoDock Vina & Glide Molecular Docking
- Predictive QSAR & Pharmacophore Modeling
- ADMET & Physicochemical Profiling
Molecular Modeling & Atomistic Dynamics
Investigate structural stability, conformational transitions, and cryptic binding pockets at atomistic resolution. GPU-accelerated GROMACS/AMBER 100ns to 1μs simulations and TTMD thermal stability calculators.
- All-Atom MD (CHARMM36m / AMBER ff19SB)
- Binding Free Energy (MM-PBSA / MM-GBSA)
- TTMD Thermal Stabilization Design
- Essential Dynamics & PCA Trajectory Analysis
Data FAIRification & Biological Curation
Cleanse, standardize, and structure fragmented biomedical datasets into Findable, Accessible, Interoperable, and Reusable (FAIR) assets. Formatted for downstream machine learning and multi-omics integration.
- Ontology Mapping & Semantic Standardization
- Multi-Modal Cohort Harmonization
- AI-Ready Feature Engineering
- Comprehensive Scientific Metadata Governance
Custom Bio-AI & Graph Neural Networks
Develop proprietary machine learning models, biological graph neural networks (GNNs), and protein language model representations (ESM-2) trained to solve your laboratory specific predictive challenges.
- Protein Language Embeddings (ESM-2, ProtBERT)
- PyTorch Geometric Graph Architectures
- Model Interpretability (SHAP, Attention Weights)
- Containerized Microservice Deployment
You Need More Than Data. That Is Why Data Means More to Us.
Discovery demands data, but not all data is equal. We bring structure to the chaos of biological data, transforming raw reads and atomistic coordinates into actionable therapeutic milestones.
More Confident Decisions
Our interdisciplinary team fuses deep life science domain expertise with cutting-edge computational technology. We apply multiple-testing corrections (Benjamini-Hochberg FDR < 0.05) and orthogonal validation so you can make confident, data-centric research decisions.
More Efficient Processes
We architect automated pipelines and containerized environments that make your computational journey shorter, simpler, and swifter. From raw FASTQ to annotated targets, our workflows eliminate bottlenecks and compress months of work into days.
More Power for Your Lab
We do not dictate rigid black-box tools. We co-design and co-create with your research team, delivering containerized Singularity/Docker images, complete source code, and full analytical audit trails for complete independence.
More Validated Discoveries
Discovery is a long shot with high attrition. Through physics-based docking of 500,000+ compounds, MM-GBSA binding free energies, and atomistic dynamics, we triage candidates down to high-affinity hits that succeed in wet-lab assays.
Tackling Critical Questions Across the Biological Continuum
Discover how our computational biology and AI pipelines address pressing biological bottlenecks, from unravelling disease mechanisms to discovering high-affinity therapeutic leads.
Our Core Computational Capabilities
Select a scientific discipline to explore our input data requirements, specialized toolchains, and validated analytical outputs.
Genomics & Transcriptomics Architecture
Unravel gene regulation, clonal evolution, and spatial heterogeneity with high-throughput sequencing pipelines optimized for bulk and single-cell datasets.
- Illumina, PacBio, and Nanopore FASTQ/BAM
- 10x Genomics Single-Cell (scRNA-seq / scATAC)
- FFPE and Fresh Frozen bulk tissue RNA-seq
- Exome and targeted capture sequencing panels
- FastQC, Trimmomatic, STAR, HISAT2
- DESeq2, edgeR, Sleuth differential analysis
- Seurat v5, Scanpy, Harmony batch integration
- GATK4 variant calling and annotation
- Publication-grade volcano, PCA, and UMAP plots
- GSEA, Reactome, and KEGG pathway enrichment
- Interactive web-based expression dashboards
- Full audit trail and containerized pipeline code
Computational Drug Design & In Silico Screening
Accelerate lead identification from millions of compounds to high-affinity drug candidates using physics-based molecular docking, machine learning QSAR, and ADMET profiling.
- Small-molecule chemical libraries (SMILES, SDF, Mol2)
- Target protein crystal or Cryo-EM coordinates (PDB, mmCIF)
- Known active/inactive training matrices for QSAR
- High-throughput screening bioassay outputs
- AutoDock Vina, Glide, Smina docking engines
- RDKit, Mordred molecular descriptor extraction
- Random Forest, XGBoost, and DeepChem QSAR
- SwissADME, pkCSM, and pk-sim pharmacokinetic models
- Ranked lead candidate tables with binding energies
- 2D/3D ligand-target interaction maps
- ADMET drug-likeness and toxicity matrices
- Wet-lab cherry-picking recommendations
Molecular Modeling & Atomistic Dynamics
Investigate structural stability, conformational transitions, and allosteric mechanisms at atomistic resolution using classical and temperature-targeted molecular dynamics.
- Wild-type and mutant protein sequences (FASTA)
- Experimentally determined or predicted PDB structures
- Membrane protein complexes and lipid bilayer topologies
- Multi-protein or protein-nucleic acid complexes
- AlphaFold3, ESMFold, and Modeller homology modeling
- GROMACS, NAMD, and AMBER simulation suites
- CHARMM36m and AMBER ff19SB force fields
- MMPBSA.py and TTMD thermal stability calculators
- RMSD, RMSF, Rg, and hydrogen-bond trajectory plots
- Binding free energy calculation (MM-PBSA/GBSA)
- Essential dynamics and principal component analysis (PCA)
- High-resolution rendered structural movies and figures
Multi-Omics Systems Biology Integration
Unify proteomics, metabolomics, epigenomics, and transcriptomics into holistic network models to decode biological mechanisms and disease drivers.
- Mass spectrometry quantitative proteomics tables
- Untargeted and targeted metabolomics profiles
- ChIP-seq, ATAC-seq, and DNA methylation matrices
- Matching clinical phenotypes and patient outcomes
- MOFA+ (Multi-Omics Factor Analysis)
- mixOmics, DIABLO, and WGCNA co-expression networks
- STRINGdb, Cytoscape, and Reactome pathway engines
- Graph embedding and network pharmacology frameworks
- Multi-layered interactive network visualization maps
- Cross-modality correlation and latent factor rankings
- Identified master regulatory hubs and biomarker signatures
- Comprehensive systems-level biological reports
Custom Bio-AI & Machine Learning Engineering
Develop proprietary machine learning models, biological graph neural networks, and automated workflows engineered for your team's specific proprietary data.
- High-content imaging and histology slide data
- Unstructured bio-literature and experimental protocols
- Molecular graph representations and SMILES tokens
- Longitudinal patient or bioreactor sensor telemetry
- PyTorch, PyTorch Geometric (GNNs), TensorFlow
- Protein Language Models (ESM-2, ProtBERT)
- Hugging Face Transformers and fine-tuning harnesses
- Docker and Singularity containerized microservices
- Trained weights with rigorous cross-validation benchmarks
- REST API or CLI tool for internal researcher adoption
- Model interpretability analysis (SHAP, attention maps)
- Complete source code repository with technical documentation
Informatics Solutions Across the Life Sciences
We partner with organizations across discovery, clinical development, and biotechnology to turn complex biological data into actionable breakthroughs.
Biopharma & Therapeutics
Accelerating discovery pipelines from initial target identification and lead triage to translational readiness. We provide virtual screening campaigns, single-cell biomarker discovery, and strict IP ring-fencing for large and emerging pharmaceutical companies.
Academic & Research Institutes
Supporting principal investigators and genomics laboratories with publication-grade differential expression, trajectory analysis, and biophysical simulations. We deliver comprehensive reports, high-resolution figures, and statistical writeups ready for peer-reviewed submission.
Biotechnology & Industrial Enzymes
Engineering robust biocatalysts and therapeutic proteins. We employ temperature-targeted molecular dynamics (TTMD) to detect thermal instability hotspots and rationally design stabilizing point mutations that elevate melting temperatures and preserve catalytic efficiency.
Our Collaborative Delivery Process
Every project proceeds through a four-stage milestone framework with formal quality control gates, ensuring complete transparency and zero guesswork.
Consultation & Biological Scoping
QC Gate: Data Viability CheckWe host a focused scientific alignment session to review your underlying biology, verify dataset integrity, check read depth and coverage metrics, and establish formal deliverables.
Pipeline Architecture & Pilot Validation
QC Gate: Benchmark ValidationOur computational biologists construct a bespoke, containerized workflow (Docker or Nextflow) and benchmark it on representative pilot data to confirm accuracy before scaled execution.
Full-Scale HPC Execution & Analysis
QC Gate: Statistical Rigor (FDR < 0.05)We process your complete dataset on our high-performance computing cluster, applying multiple testing corrections, sensitivity analyses, and strict quality control thresholds.
Synthesis, Deliverables & Post-Project Support
QC Gate: Final Science ReviewYou receive interactive dashboards, publication-grade figures, fully documented source code, and comprehensive written reports, backed by ongoing support for manuscript revisions.
Proven Scientific Track Record
Real-world engagements where our computational analyses unlocked novel biological insights, optimized drug leads, and accelerated publication timelines.
Trusted by Life Science Researchers
Read how our computational partnerships have supported wet-lab validation and accelerated scientific publications.
"bioinfoLink transformed our complex RNA-seq dataset into publication-ready results in under three weeks. Their single-cell clustering identified two novel cell subpopulations that we had completely overlooked. The quality of their differential expression analysis and figures was exceptional."
"Their molecular docking and MD simulation workflow was decisive for our drug repurposing campaign. bioinfoLink triaged 50,000+ compounds down to 12 high-confidence leads, three of which showed biological activity in our initial in vitro assays. Outstanding execution."
"We partnered with bioinfoLink for a multi-omics study combining mass-spec proteomics, metabolomics, and RNA-seq. Their network integration revealed pathway interactions that standard packages missed. They are true scientific peers who understand the biological stakes."
About bioinfoLink
Founded in 2024, bioinfoLink was born from a conviction that world-class computational biology should be accessible to every research team, not just those with seven-figure infrastructure budgets. Our founding team brings collective experience spanning academic genomics laboratories, pharmaceutical R&D pipelines, and high-performance computing centers. We witnessed firsthand how discovery stalls when research groups lack scalable computational infrastructure or specialized bioinformatics expertise - and we built bioinfoLink to eliminate that bottleneck entirely.
Today, our interdisciplinary team of PhD-level scientists spans computational genomics, structural biophysics, cheminformatics, and machine learning engineering. We are advised by principal investigators from leading research institutions to ensure our methodologies remain at the frontier. We deliver the depth and rigor of an elite in-house computational unit - without the hiring overhead, onboarding delays, or infrastructure capital expenditure.
Scientific Innovation
Analytical Excellence
Collaborative Trust
Data Integrity
Connect with Our Computational Team
Consult directly with PhD-level computational biologists with deep experience in academic research and pharmaceutical R&D. Submit an intake brief or reach out directly.
Project Scoping Inquiry
Submit your biological objectives, target deadlines, and raw data types to receive a structured feasibility assessment within 24 hours.