Search 250 Million Papers Across 12+ Academic Databases
One search, every source. Find papers from PubMed, Semantic Scholar, OpenAlex, arXiv, bioRxiv, ClinicalTrials.gov, Orphanet, OMIM, and more. AI-powered relevance ranking brings the most important papers to the top.
Searching multiple databases separately wastes hours of your time
Most researchers start their literature search in PubMed. Then they switch to Semantic Scholar for citation-based discovery. Then to Google Scholar for broader coverage. Then to arXiv or bioRxiv for preprints. Each database has its own interface, its own query syntax, and its own way of presenting results. Keeping track of which papers you have already seen across five or six different search engines is a frustrating, error-prone process.
Worse, important papers often live in specialized databases that researchers do not think to check. A rare disease paper indexed in Orphanet or OMIM might never appear in a standard PubMed search. A clinical trial registered on ClinicalTrials.gov might have results that are not yet published in a journal article. Preprints on bioRxiv or medRxiv might contain findings that will not appear in PubMed for months.
NousLab solves this by searching all 12+ databases simultaneously and merging the results into a single, deduplicated, AI-ranked list. You search once and see everything.
Traditional search vs NousLab
How paper discovery works
From research question to imported papers in four steps. One search replaces hours of manual database hopping.
Enter your query
Type your research question, topic keywords, or paste a DOI, PubMed ID, or arXiv ID directly into the unified search bar.
Search all sources
NousLab queries PubMed, Semantic Scholar, OpenAlex, Crossref, Europe PMC, DOAJ, arXiv, bioRxiv, ClinicalTrials.gov, Orphanet, OMIM, and more simultaneously.
AI ranks results
Results are merged, deduplicated, and ranked by AI based on relevance to your query, publication recency, and source authority. Filter by source, date, or relevance score.
Import and analyze
Select the papers you need and batch import them into your project. Imported papers are automatically queued for AI analysis to extract methodology, results, and quantitative data.
Academic databases covered
From the largest general-purpose indexes to specialized rare disease registries, NousLab covers the sources that matter for biomedical and scientific research.
General Academic
- •PubMed
- •PubMed Central
- •Semantic Scholar
- •OpenAlex
- •Crossref
- •Europe PMC
- •DOAJ
Preprints
- •arXiv
- •bioRxiv
- •medRxiv
Access the latest research before it goes through peer review. Preprints often contain findings months ahead of journal publication.
Rare Disease and Clinical
- •ClinicalTrials.gov
- •Orphanet
- •OMIM
Specialized sources for rare diseases and clinical trials that are often missed in standard academic searches.
Built for how researchers actually search
Every feature is designed to reduce the time between having a research question and having the papers you need in your project.
Unified Search
One search bar, 12+ databases. No more switching between PubMed, Semantic Scholar, and Google Scholar. Results are automatically deduplicated so you never see the same paper twice from different sources.
AI Relevance Ranking
After retrieving results, AI scores each paper based on how closely it matches your research question. The most relevant papers surface first, saving you from scrolling through hundreds of loosely related results.
Batch Import
Select multiple papers from your search results and import them into your project with one click. Up to 50 papers per batch. Imported papers are automatically queued for AI analysis.
Source and Date Filtering
Filter results by database source, publication date range, or relevance score. A sticky results header keeps your filter controls visible as you browse through hundreds of results.
Preprint Access
Search arXiv, bioRxiv, and medRxiv alongside peer-reviewed databases. Find the latest findings months before they appear in journals. Preprint results are clearly labeled so you always know the publication status.
Rare Disease Databases
Search Orphanet, OMIM, and ClinicalTrials.gov alongside general academic databases. Essential for rare disease researchers who need to find literature across specialized and general sources without running separate searches.
How a rare disease researcher uses paper discovery
A clinical geneticist is investigating a rare metabolic disorder with fewer than 200 known cases worldwide. The standard PubMed search returns only 14 results. Most of the existing knowledge is scattered across Orphanet disease profiles, OMIM gene entries, case reports in small European journals indexed in Europe PMC, and a handful of bioRxiv preprints from specialized labs.
Using NousLab's Paper Discovery, the researcher enters the disorder name and searches all 12+ databases simultaneously. The results include the 14 PubMed papers, 3 additional papers from Europe PMC not indexed in PubMed, the Orphanet disease profile with linked publications, 2 OMIM entries with associated gene-phenotype relationships, a registered clinical trial on ClinicalTrials.gov testing a potential treatment, and a bioRxiv preprint describing a new animal model for the condition.
AI relevance ranking places the most directly relevant papers at the top. The researcher selects 23 papers and imports them into a NousLab project. Within minutes, the AI has analyzed each paper and extracted the key clinical data, genetic variants, treatment outcomes, and molecular pathways.
What previously required searching five different databases over two days is now completed in a single session. The researcher has a comprehensive view of all published evidence for the disorder, including sources they would not have thought to check.
Frequently asked questions
Which academic databases does NousLab search?
NousLab searches 12+ academic databases simultaneously: PubMed, PubMed Central, Semantic Scholar, OpenAlex, Crossref, Europe PMC, DOAJ, arXiv, bioRxiv/medRxiv, ClinicalTrials.gov, Orphanet, and OMIM. This covers general academic literature, preprints, rare disease resources, and clinical trial registries in a single query.
How does AI relevance ranking work?
After retrieving results from all databases, NousLab uses AI to score each paper based on how closely it matches your research question. The ranking considers title relevance, abstract content, publication recency, citation count, and source authority. You can filter and re-sort results by source, date, or relevance score.
Can I search for preprints and clinical trials?
Yes. NousLab includes arXiv, bioRxiv, and medRxiv for preprints, and ClinicalTrials.gov for registered clinical trials. This means you can find the latest research before it goes through peer review, and identify ongoing or completed clinical trials related to your topic.
How many papers can I import at once?
You can select and import up to 50 papers at once from the search results into your NousLab project. Imported papers are automatically queued for AI analysis, so you can go from discovery to structured data without leaving the platform.
Does NousLab support rare disease research?
Yes. NousLab integrates Orphanet and OMIM, two of the most important rare disease databases. You can search for rare disease papers alongside general biomedical literature in PubMed and Europe PMC, ensuring you do not miss relevant publications from specialized sources.
Can I import papers by DOI or PubMed ID without searching?
Yes. In addition to the discovery search, you can import individual papers directly using DOI, PubMed ID (PMID), arXiv ID, or author name. NousLab retrieves the full metadata and, when available, the full text for analysis. This is useful when you already know exactly which papers you need.
Ready to search smarter, not harder?
See how NousLab can help your team find every relevant paper across 12+ academic databases in a single search.
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