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GRKRaj.Org - Lecture Notes for Masters and PreUniversity Students — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Biological Sciences →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
barberlab.org ↗	65 match 1 shared topics	Barber lab – University of Oregon	en	biological-sciences WordPress	robotsllmsaihumans	emailphone	none
favelalab.com ↗	65 match 1 shared topics	Favela Lab \| University of Arizona	en	biological-sciences Wix	robots llmsaihumans	emailphone	none
barnhartlab.org ↗	65 match 1 shared topics	The Barnhart Lab – at Columbia University	en	biological-sciences WordPress	robotsllmsaihumans	emailphone	none
avandyke.com ↗	65 match 1 shared topics	Van Dyke Lab @ Fairfield Universiy	en	biological-sciences Wix	robotsllmsaihumans	emailphone	none
baumslab.org ↗	64 match 1 shared topics	Baums Laboratory \| Helmholtz Institue for Functional Marine Biodiversity \| Research in Coral Ecology and Evolution	en	biological-sciences	robotsllmsaihumans	emailphone	none
avianevonus.com ↗	64 match 1 shared topics	Avian Evolution Lab – National University of Singapore	en	biological-sciences WordPress	robotsllmsaihumans	emailphone	none
basmycology.com ↗	64 match 1 shared topics	Agar Media & Liquid Culture For Mycology \| Bas Mycology	en	biological-sciences WordPress WooCommerce	robotsllmsaihumans	emailphone	none
bdcherringtonlab.org ↗	64 match 1 shared topics	Cherrington Lab – University of Wyoming, Department of Zoology and Physiology	en	biological-sciences WordPress	robotsllmsaihumans	emailphone	none
susanlovesscience.com ↗	64 match 1 shared topics	Dr. Susan Villarreal, Entomologist, Denison University, Biology Department	en	biological-sciences	robotsllmsaihumans	emailphone	none
apg.asn.au ↗	64 match 1 shared topics	Adelaide Protein Group – A special interest group of the Australian Society for Biochemistry and Molecular Biology	AU en	biological-sciences WordPress	robotsllmsaihumans	emailphone	none
pires-lab.com ↗	64 match 1 shared topics	Pires Laboratory University of Virginia \| Peptidoglycan \| Fluorescent Probes	en	biological-sciences Wix	robots llmsaihumans	emailphone	none
urbanmedicalento.com ↗	64 match 1 shared topics	University of Hawaiʻi at Mānoa - Urban & Medical Entomology Lab	en	biological-sciences WordPress	robotsllmsaihumans	emailphone	none
digisporesmd.com ↗	64 match 1 shared topics	Mushroom Spores & Spore Syringes for Microscopy \| SporesMD	en	biological-sciences WordPress WooCommerce	robots llmsaihumans	emailphone	none
abu-remaileh.com ↗	64 match 1 shared topics	Abu-Remaileh Lab @ Stanford University \| Lysosome \| Metabolism \| Calif	en	biological-sciences Wix	robotsllmsaihumans	emailphone	none
happysporesmd.com ↗	64 match 1 shared topics	Mushroom Spores & Spore Syringes for Microscopy \| SporesMD	en	biological-sciences WordPress WooCommerce	robotsllmsaihumans	emailphone	none
luyiwangtw.com ↗	63 match 1 shared topics	Lu-Yi Wang \| Research Fellow, Centre of Excellence for Biosecurity Risk Analysis (CEBRA). The University of Melbourne, Australia	en	biological-sciences WordPress	robotsllmsaihumans	emailphone	none
sampaplauskas.com ↗	63 match 1 shared topics	Paplauskas, Sam – Ponds, predators and parasites	en	biological-sciences WordPress	robotsllmsaihumans	emailphone	none
faunomics.com ↗	63 match 1 shared topics	Faunomics: Exploring biodiversity with eDNA services	en	biological-sciences WordPress	robotsllmsaihumans	emailphone	none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.