LEADER 01911nam 2200517I 450 001 9910704921003321 005 20131218163548.0 035 $a(CKB)5470000002446538 035 $a(OCoLC)865557393 035 $a(EXLCZ)995470000002446538 100 $a20131218d1986 ua 0 101 0 $aeng 135 $aurbn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aOnboard processing satellite network architecture and control study /$fprepared by S. Joseph Campanella, Benjamin A. Pontano and Harvey Chalmers 210 1$aClarksburg, Maryland :$cComsat Laboratories ;$aCleveland, OH :$cNASA Lewis Research Center,$d[1987] 215 $a1 online resource (206 unnumbered pages) $cillustrations 225 1 $aContractor report ;$v180817 300 $aTitle from title screen (viewed on Dec. 18, 2013). 300 $a"June 1987." 320 $aIncludes bibliographical references (pages [194-195]). 606 $aArchitecture (computers)$2nasat 606 $aFrequency division multiple access$2nasat 606 $aOnboard data processing$2nasat 606 $aPacket switching$2nasat 606 $aTime division multiple access$2nasat 606 $aTime division multiplexing$2nasat 615 7$aArchitecture (computers) 615 7$aFrequency division multiple access. 615 7$aOnboard data processing. 615 7$aPacket switching. 615 7$aTime division multiple access. 615 7$aTime division multiplexing. 700 $aCampanella$b S. Joseph$01390800 702 $aPontano$b Benjamin A. 702 $aChalmers$b Harvey 712 02$aCOMSAT Laboratories, 712 02$aLewis Research Center, 801 0$bGPO 801 1$bGPO 906 $aBOOK 912 $a9910704921003321 996 $aOnboard processing satellite network architecture and control study$93443858 997 $aUNINA LEADER 04517nam 22011413a 450 001 9910346689103321 005 20250203235436.0 010 $a9783039211647 010 $a3039211641 024 8 $a10.3390/books978-3-03921-164-7 035 $a(CKB)4920000000094778 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/53322 035 $a(ScCtBLL)2017631d-2dac-4d67-8b55-73ccb5c98cb9 035 $a(OCoLC)1126184144 035 $a(oapen)doab53322 035 $a(EXLCZ)994920000000094778 100 $a20250203i20192019 uu 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aMethods in Computational Biology$fRoss Carlson, Herbert Sauro 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2019 210 1$aBasel, Switzerland :$cMDPI,$d2019. 215 $a1 electronic resource (214 p.) 311 08$a9783039211630 311 08$a3039211633 330 $aModern biology is rapidly becoming a study of large sets of data. Understanding these data sets is a major challenge for most life sciences, including the medical, environmental, and bioprocess fields. Computational biology approaches are essential for leveraging this ongoing revolution in omics data. A primary goal of this Special Issue, entitled "Methods in Computational Biology", is the communication of computational biology methods, which can extract biological design principles from complex data sets, described in enough detail to permit the reproduction of the results. This issue integrates interdisciplinary researchers such as biologists, computer scientists, engineers, and mathematicians to advance biological systems analysis. The Special Issue contains the following sections:?Reviews of Computational Methods?Computational Analysis of Biological Dynamics: From Molecular to Cellular to Tissue/Consortia Levels?The Interface of Biotic and Abiotic Processes?Processing of Large Data Sets for Enhanced Analysis?Parameter Optimization and Measurement 606 $aInformation technology industries$2bicssc 610 $ainosine 610 $aimmune checkpoint inhibitor 610 $ageometric singular perturbation theory 610 $asimulation 610 $aBioModels Database 610 $aADAR 610 $acalcium current 610 $abifurcation analysis 610 $abacterial biofilms 610 $anonlinear dynamics 610 $aexplanatory model 610 $aturning point bifurcation 610 $aoscillator 610 $aworkflow 610 $abioreactor integrated modeling 610 $amodeling methods 610 $aelementary flux modes visualization 610 $amultiscale systems biology 610 $aevolutionary algorithm 610 $ametabolic model 610 $adifferential evolution 610 $areduced-order model 610 $acomputational model 610 $agut microbiota dysbiosis 610 $acanard-induced EADs 610 $acomputational biology 610 $ametabolic modelling 610 $amethods 610 $aSREBP-2 610 $amechanistic model 610 $asystems modeling 610 $abiological networks 610 $amacromolecular composition 610 $aprovenance 610 $aflux balance analysis 610 $aimmunotherapy 610 $acompartmental modeling 610 $aimmuno-oncology 610 $ametabolic network visualization 610 $amechanism 610 $abistable switch 610 $aClostridium difficile infection 610 $abioreactor operation optimization 610 $amicroRNA targeting 610 $aCFD simulation 610 $abiomass reaction 610 $aRNA editing 610 $aordinary differential equation 610 $ametabolic modeling 610 $amass-action networks 610 $ahybrid model 610 $amultiple time scales 610 $aquantitative systems pharmacology (QSP) 610 $amathematical modeling 610 $amicroRNA 610 $acancer 610 $aparameter optimization 610 $aHopf bifurcation 610 $abreast 615 7$aInformation technology industries 700 $aCarlson$b Ross$01318727 702 $aSauro$b Herbert 801 0$bScCtBLL 801 1$bScCtBLL 906 $aBOOK 912 $a9910346689103321 996 $aMethods in Computational Biology$93033491 997 $aUNINA