Robot | Path | Permission |
GoogleBot | / | ✔ |
BingBot | / | ✔ |
BaiduSpider | / | ✔ |
YandexBot | / | ✔ |
Title | Linnarsson |
Description | Sten Linnarsson is a Professor of Molecular Systems Biology at <a href=’http://ki.se’>Karolinska |
Keywords | N/A |
WebSite | linnarssonlab.org |
Host IP | 185.199.111.153 |
Location | - |
Site | Rank |
US$2,170,130
Last updated: 2023-05-16 04:21:30
linnarssonlab.org has Semrush global rank of 4,877,267. linnarssonlab.org has an estimated worth of US$ 2,170,130, based on its estimated Ads revenue. linnarssonlab.org receives approximately 250,400 unique visitors each day. Its web server is located in -, with IP address 185.199.111.153. According to SiteAdvisor, linnarssonlab.org is safe to visit. |
Purchase/Sale Value | US$2,170,130 |
Daily Ads Revenue | US$2,004 |
Monthly Ads Revenue | US$60,096 |
Yearly Ads Revenue | US$721,151 |
Daily Unique Visitors | 16,694 |
Note: All traffic and earnings values are estimates. |
Host | Type | TTL | Data |
linnarssonlab.org. | A | 3599 | IP: 185.199.111.153 |
linnarssonlab.org. | A | 3599 | IP: 185.199.110.153 |
linnarssonlab.org. | A | 3599 | IP: 185.199.108.153 |
linnarssonlab.org. | A | 3599 | IP: 185.199.109.153 |
linnarssonlab.org. | AAAA | 3599 | IPV6: 2606:50c0:8003::153 |
linnarssonlab.org. | AAAA | 3599 | IPV6: 2606:50c0:8000::153 |
linnarssonlab.org. | AAAA | 3599 | IPV6: 2606:50c0:8002::153 |
linnarssonlab.org. | AAAA | 3599 | IPV6: 2606:50c0:8001::153 |
linnarssonlab.org. | NS | 3600 | NS Record: ns1.dnsimple.com. |
linnarssonlab.org. | NS | 3600 | NS Record: ns2.dnsimple.com. |
linnarssonlab.org. | NS | 3600 | NS Record: ns3.dnsimple.com. |
linnarssonlab.org. | NS | 3600 | NS Record: ns4.dnsimple.com. |
linnarssonlab.org. | TXT | 3600 | TXT Record: ALIAS for linnarsson-lab.github.io |
Linnarsson Lab Publications Data Tools People Contact We are entering a transformational period in biomedical research, where technologies to read and write biological information have finally reached the scale and complexity of the organs we study. Gene editing, synthetic biology, synthetic vectors, single-cell biology, AI and machine learning are all converging to a new paradigm of biomedical research. These developments are nothing short of revolutionary. Programmable drugs based on synthetic DNA and RNA will soon become the dominant class of medicines. They are poised to democratize drug development, radically narrowing the gap between basic discovery and clinical trial. Being fully synthetic, and programmable, they can be designed and engineered, instead of serendipitously discovered. We are learning to program our own cells, and this new power will radically define the future of human health and well-being. Our research focuses on single-cell biology, in particular applying |
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