RESEARCH SERVICES

Find a computational service by research question

Browse eight research areas, focused topics or keywords to review method choices, input requirements, quality controls and concrete deliverables.

Showing 16 of 90 research services

Omics and AIOmics data analysis

Bioinformatics and multi-omics

Start from study design and quality control, then connect statistical testing, pathways, networks and biological interpretation.

QC, normalisation and batch assessmentDifferential, enrichment and network analysisMulti-omics integration and external validation

Primary deliveryQC and statistical report

Omics and AIOmics data analysis

Single-cell and spatial omics

Start with sample and sequencing QC, then resolve cell populations, state trajectories, spatial neighbourhoods and associations in tissue microenvironments.

Single-cell QC, integration and annotationTrajectories, cell communication and regulatory networksSpatial deconvolution, neighbourhoods and multimodal integration

Primary deliveryQC, cell atlas and annotation evidence

Omics and AISystems biology and AI

AI bioinformatics

Use biological foundation models and machine learning through task adaptation, baseline comparison and uncertainty assessment.

Sequence, cell and multi-omics representationsTransfer learning and task adaptationCross-validation, calibration and interpretation

Primary deliveryBaseline and model comparison

Omics and AISystems biology and AI

AI virtual cells and perturbation prediction

Use single-cell and multi-omics representations for genetic or chemical perturbation scenarios that generate experimental priorities and testable hypotheses.

Cell and gene representation learningPerturbation scenarios and counterfactual modellingSensitivity, pathway and external-data review

Primary deliveryEstimated state shifts under defined scenarios

Omics and AIOmics data analysis

Genomics and transcriptomics analysis

Build an end-to-end path from raw-data QC to statistical interpretation and external validation for variation, expression and regulation.

Sequencing QC, alignment, quantification and variant callingDifferential expression, splicing and co-expressionFunctional annotation, enrichment and regulatory networks

Primary deliveryQC, quantification and statistical results

Omics and AIOmics data analysis

Proteomics, metabolomics and lipidomics

Start from feature tables and identification evidence, handling batch, missingness and annotation uncertainty to connect molecular changes, pathways and phenotypes.

Feature-table QC, normalisation and missingness assessmentDifferential, clustering and multivariate statisticsMolecular annotation, pathway mapping and multi-omics integration

Primary deliveryData-quality and batch diagnostics

Omics and AISystems biology and AI

Network pharmacology and target-mechanism analysis

Integrate compound, target, disease and pathway evidence into traceable multi-target hypotheses and experimental priorities.

Target prediction and evidence gradingDisease genes, PPI and pathway networksTopology, enrichment and mechanism-module analysis

Primary deliverySource-traceable target evidence table

Omics and AIOmics data analysis

Epigenomics analysis

Analyse condition-associated epigenetic regulation through chromatin accessibility, histone marks, DNA methylation and regulatory elements.

Sequencing QC and alignmentPeak or differential-methylation analysisRegulatory-element, motif and multi-omics integration

Primary deliveryQC and normalised outputs

Omics and AIOmics data analysis

mRNA expression analysis

Process raw RNA sequencing or expression matrices through QC, quantification, differential expression, splicing and functional interpretation.

Read QC, alignment and quantificationDifferential-expression and splicing analysisEnrichment, network and external-data review

Primary deliveryQC and expression matrix

Omics and AIOmics data analysis

microRNA analysis

Analyse small-RNA expression, differential microRNAs, candidate targets and pathways with mRNA or phenotype cross-validation.

Small-RNA QC and quantificationDifferential-microRNA analysisTarget prediction with anticorrelation and pathway integration

Primary deliverymicroRNA expression and QC

Omics and AIOmics data analysis

Microbiome and metagenomics analysis

Assess community composition, functional potential, differential features and host-phenotype associations from amplicon or metagenomic data.

Sequence QC and contamination reviewTaxonomic and functional profilingDiversity, compositional and association analysis

Primary deliveryQC and taxonomic or functional matrices

Omics and AISystems biology and AI

Biomarker and target identification

Integrate phenotype, omics, genetics and external evidence while separating predictive performance, mechanistic association and intervention feasibility.

Differential and multivariable screeningNested validation and feature stabilityGenetic, pathway and tractability evidence integration

Primary deliveryTiered biomarker or target candidates

Omics and AIBiostatistics

Survival analysis

Analyse research time-to-event outcomes around event definitions, follow-up, censoring and covariates, with effect estimates, assumption checks and uncertainty.

Kaplan–Meier and competing-risk descriptionCox or parametric survival modelsProportional-hazards, calibration and internal validation

Primary deliverySurvival curves and effect estimates

Omics and AIBiostatistics

Research clinical-data analysis

Analyse de-identified research datasets through data dictionaries, descriptive statistics, association models and sensitivity analyses for research rather than care decisions.

Data-dictionary and missingness auditStatistical analysis plan and modelsConfounding, sensitivity and subgroup analysis

Primary deliveryAnalysis dataset and QC records

Omics and AISystems biology and AI

Gene co-expression network analysis

Identify coordinated expression modules and relate them to phenotypes, cell states and functional pathways.

Expression filtering and covariate adjustmentCorrelation or weighted co-expression networksModule–trait and hub-stability analysis

Primary deliveryCo-expression modules

Omics and AISystems biology and AI

Gene regulatory network analysis

Infer condition-associated candidate regulation by integrating expression, regulatory elements, transcription-factor motifs and optional perturbation data.

Expression and regulatory-feature preparationNetwork inference and motif supportPerturbation or external-atlas cross-validation

Primary deliveryCandidate regulatory network

START WITH THE QUESTION

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