LEADER 02300nam 2200361 450 001 9910597903603321 005 20230219120625.0 035 $a(CKB)4100000003666497 035 $a(NjHacI)994100000003666497 035 $a(EXLCZ)994100000003666497 100 $a20230219d2018 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aToxins in Drug Discovery and Pharmacology /$fedited by Steve Peigneur 210 1$aBasel, Switzerland :$cMDPI - Multidisciplinary Digital Publishing Institute,$d2018. 215 $a1 online resource (316 pages) 311 $a3-03842-861-2 330 $aVenoms from marine and terrestrial animals (cone snails, scorpions, spiders, snakes, centipedes, cnidarian, etc.) can be seen as an untapped cocktail of biologically-active compounds, being increasingly recognized as new emerging source of peptide-based therapeutics. Venomous animals are considered to be specialized predators that have evolved the most sophisticated peptide chemistry and neuropharmacology for their own biological purposes by producing venoms that contains a structural and functional diversity of neurotoxins. These neurotoxins have shown to be highly selective ligands for a wide range of ion channels and receptors. Therefore, they represent interesting lead compounds for the development of, for example, analgesics, anti-cancer drugs, drugs for neurological disorders such as multiple sclerosis, Parkinson's disease, Alzheimer's disease, etc. This Special Issue of Toxins aims to provide a comprehensive look at toxins and toxin inspired leads and will focus on the mechanism of action, structure-function and evolution of pharmacological interesting venom components, including but not limited to, recent developments relating to the emergence of venoms as an underutilized source of highly evolved bioactive peptides with clinical potential. 606 $aPharmacology 606 $aToxins 615 0$aPharmacology. 615 0$aToxins. 676 $a615.373 702 $aPeigneur$b Steve 801 0$bNjHacI 801 1$bNjHacl 906 $aBOOK 912 $a9910597903603321 996 $aToxins in Drug Discovery and Pharmacology$92929121 997 $aUNINA LEADER 01863nam 2200493 450 001 9910520081303321 005 20231103180034.0 010 $a981-16-6768-3 010 $a9789811667688$b(eBook) 035 $a(MiAaPQ)EBC6838752 035 $a(Au-PeEL)EBL6838752 035 $a(CKB)20275204600041 035 $a(OCoLC)1291272166 035 $a(EXLCZ)9920275204600041 100 $a20220906h20212021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial intelligence and machine learning in public healthcare $eopportunities and societal impact /$fKC Santosh, Loveleen Gaur 210 1$aSingapore :$cSpringer,$d[2021] 210 4$dİ2021 215 $a1 online resource (xxiii, 74 pages) $cillustrations 225 1 $aSpringerBriefs in applied sciences and technology, Computational intelligence,$x2625-3712 311 08$aPrint version: Santosh, K. C. Artificial Intelligence and Machine Learning in Public Healthcare Singapore : Springer Singapore Pte. Limited,c2021 9789811667671 320 $aIncludes bibliographical references. 410 0$aSpringerBriefs in applied sciences and technology.$pComputational intelligence. 606 $aArtificial intelligence$xMedical applications 606 $aPublic health$xData processing 606 $aMachine learning 615 0$aArtificial intelligence$xMedical applications. 615 0$aPublic health$xData processing. 615 0$aMachine learning. 676 $a006.31 700 $aSantosh$b K. C.$01074647 702 $aGaur$b Loveleen 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910520081303321 996 $aArtificial intelligence and machine learning in public healthcare$92911516 997 $aUNINA