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Doudna_pages 1..9
https://haseloff.plantsci.cam.ac.uk/resources/Part2SynBio_refs/Lecture-1/Doudna2014.pdf14 Aug 2023: CRISPRm consists of the op-timization of CRISPR-Cas9 to generate quantita-tive gene assembly and DNA library insertioninto the fungal genomes, providing a strategy toimprove the activity of biomolecules. -
FEMS Yeast Research, 15, 2015, 1–10 doi:…
https://haseloff.plantsci.cam.ac.uk/resources/Part2SynBio_refs/Lecture-2/Jensen2015.pdf14 Aug 2023: particularly when op-timizing metabolic pathway flux without easy detectable phe-notypes. ... Curran KA, Karim AS, Gupta A, Alper HS Use of expression-enhancing terminators in Saccharomyces cerevisiae to increasemRNA half-life and improve gene expression -
GMO-cover-100920.indd
https://haseloff.plantsci.cam.ac.uk/resources/SynBio_reports/a-decade-of-eu-funded-gmo-research_en.pdf14 Aug 2023: Food, Agriculture & Fisheries & Biotechnology. E U R O P E A NCOMMISSION. European Research Area. PROJECT INFORMATION. A decade of EU-funded GMO research. (2001 - 2010). KI. NA. This publication summarises the results of 50 selected research -
Plant ScienceResearch Network Plant Science Decadal Vision…
https://haseloff.plantsci.cam.ac.uk/resources/SynBio_reports/DECADAL-VISION-2020-FINAL-sm.pdf14 Aug 2023: Plant ScienceResearch Network. Plant Science Decadal Vision 2020–2030Reimagining the Potential of Plants for a Healthy and Sustainable Future. How to Cite: Henkhaus N, Bartlett M, Gang D, et al. Plant Science Decadal Vision 2020–2030: -
Preparing for Future Products of Biotechnology
https://haseloff.plantsci.cam.ac.uk/resources/SynBio_reports/NAS_FutureProducts_24605.pdf14 Aug 2023: op, symposiu are those o. mittee, or the. cademies, ple. experts. -
Copyright © National Academy of Sciences. All rights reserved. ...
https://haseloff.plantsci.cam.ac.uk/resources/SynBio_reports/Naturesinspiration.pdf14 Aug 2023: Accessed online 28 July 2009. Ro DK, Paradise EM, Ouellet M, Fisher KJ, Newman KL, Ndungu JM, Ho KA, Eachus RA, Ham TS, Kirby J, Chang M, Withers ST, Shiba Y, -
2010SPGCE001 final edit
https://jotter.educ.cam.ac.uk/volume2/001-050-yevsiyevichy/001-050-yevsiyevichy.pdf23 Dec 2010: t wou. ld op. pose. the. Just. War. the. ory? Why? •. ... lism. • How. wou. ld Ka. nt re. spon. d to t. -
OP-BRAI140256 1..7
https://laser.ceb.cam.ac.uk/system/files/documents/brain-frischi-2014.pdfJ. Alzheimers Dis. 2010; 21: 81–6.Johnson KA, Fox NC, Sperling RA, Klunk WE. ... dysfunction. Neurobiol Dis 2009; 35: 352–8. Villemagne VL, Burnham S, Bourgeat P, Brown B, Ellis KA, Salvado O,. -
Cambridge Alumni Magazine Issue 84 – Easter 2018 What ...
https://magazine.alumni.cam.ac.uk/wp-content/uploads/2020/01/00_cam_84_singles_lo_res_hyperlinks_v3_0.pdf29 Jan 2020: OP. : JO. E S. NO. W; R. AC. HE. L W. ... TR. AT. ION. : KA. TE. CO. PE. LA. ND. CAM 84 | EASTER 2018. -
Dr Leonardo Bottolo - Department of Medical Genetics
https://medgen.medschl.cam.ac.uk/dr-leonardo-bottolo/Recent publications. McGurk KA, Zhang X, Theotokis P, Thomson K, Harper A, Buchan RJ, et al. -
Professor Eamonn Maher - Department of Medical Genetics
https://medgen.medschl.cam.ac.uk/professor-eamonn-maher/Narasimhan VM, Hunt KA, Mason D, Baker CL, Karczewski KJ, Barnes MR, et al. -
Efficient Reinforcement Learning using Gaussian Processes
https://mlg.eng.cam.ac.uk/pub/pdf/Dei10.pdf13 Feb 2023: One op-tion to make the model more flexible is to add parameters to φ, which we thinkthey may be of importance. ... Maximizing the evidence using equation (2.24) is a nonlinear, non-convex op-timization problem. -
Bayesian Time Series Learning with Gaussian Processes Roger…
https://mlg.eng.cam.ac.uk/pub/pdf/Fri15.pdf13 Feb 2023: Bayesian Time Series Learning. with Gaussian Processes. Roger Frigola-AlcaldeDepartment of Engineering. St Edmund’s CollegeUniversity of Cambridge. August 2015. This dissertation is submitted for the degree ofDoctor of Philosophy. SUMMARY. The -
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https://mlg.eng.cam.ac.uk/pub/pdf/GoeRasToletal04.pdf13 Feb 2023: PYáN247L,I <7=Ka 246 2UI > I > 573T3 ã D < 6NL.246 abN= LL,I a L áI? ... DFE MÛUØUZJLNYZMSM 62TJ;á <7=Ka 5X6 a 24II > LÒ246 > Im246 VGM 24IÌà bN<Y< Im246. -
Scalable Inference for StructuredGaussian Process Models Yunus…
https://mlg.eng.cam.ac.uk/pub/pdf/Saa11.pdf13 Feb 2023: namely that if:. p. ([a. b. ])= N. ([µa. µb. ],. [Ka,a Ka,b. Kb,a Kb,b. ]), (1.17). then the means and covariances of marginals are simply the relevant subvectors ... and. submatrices of the joint mean and covariance respectively, i.e., p(a) = N(µa, Ka -
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https://mlg.eng.cam.ac.uk/zoubin/papers/compmod.pdf27 Jan 2023: MN w,XU4QTgU4%Xc_ 4[VQT]4Q;]QZ46[dU N op_[VU VQTa%od[V%D[dQ][VUOva N dUDU_ ZX[ZgV N ... $ %'&. Op. tim. al. Mix. ing. Pro. po. rtio. -
gppl.dvi
https://mlg.eng.cam.ac.uk/zoubin/papers/icml05chuwei-pl.pdf27 Jan 2023: This definition of tun-able variables is helpful to convert the constrained op-timization problem into an unconstrained optimizationproblem. ... ǩt = [Ka(xt, x1), Ka(xt, x2),. , Ka(xt, xn)].5 Themean of the predictive distribution P(fa(xt)|E, θ) canbe -
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https://mlg.eng.cam.ac.uk/zoubin/papers/ijprai.pdf27 Jan 2023: "# %$&' )(,-/.012)34,6578:9; #"<. =?>A@ BDCFEHGJI8KLIDM4KLNOKLEDCGPK:Q4R4BTSHU2>ANWVD@ QXK:QXCY>AE8KLZ?[]@ M4>AR_]CFED]baE CYQ. acEDCYdL]M4R_CYQSHU2>LZFZFeAPf%>AEDgD>LEf%>AEDg >AEihjUkl[nmLoprq8sEDeLZtKLEDg. u3vvTw<x4yy{zzz<|}Lv||! |8yL8)yD3) T} Lvl2 -
� � � � � ����� ��� ���� ��� ...
https://mlg.eng.cam.ac.uk/zoubin/papers/nlds_preprint.pdf27 Jan 2023: "# $% #&'() ,-$ '.$0/1,324 2. 5&6708:9<;>=@?BA@CED9GFIHJ?LKMONP6NJQR67S6KJ? TPUWVYX[Z]_X[acb!dfehgjiRkhlnmodqp:r@isktdRu'vWiwuyxwz{l|iwr}ziz@d>ehgji<u|dR itvlyqxhuzpr@diwxovu|dvWz{lyqpszlnr@Ez{@dxhro@r@isreoptgjp>d_zjdg{vpromhl|m@modRr:vzpszjdvEitpqr -
Member: John T O’Brien - Cambridge Neuroscience
https://neuroscience.cam.ac.uk/member/jto27/Journal: Brain. E-pub date: 1 Aug 2023. Authors: M Malpetti, TE Cope, D Street, PS Jones, FH Hezemans, E Mak, KA Tsvetanov, T Rittman, WR Bevan-Jones, K Patterson, L ... Journal: J Nucl Med. E-pub date: 1 Jul 2022. Authors: M Malpetti, SS Kaalund, KA
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