메뉴 건너뛰기




Volumn 35, Issue 8, 2017, Pages 743-755

How Not To Drown in Data: A Guide for Biomaterial Engineers

Author keywords

biomaterials; in silico screening; machine learning; modeling

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL METHODS; EDUCATION; GENE EXPRESSION; LEARNING ALGORITHMS; LEARNING SYSTEMS; MODELS;

EID: 85021745740     PISSN: 01677799     EISSN: 18793096     Source Type: Journal    
DOI: 10.1016/j.tibtech.2017.05.007     Document Type: Review
Times cited : (35)

References (79)
  • 1
    • 84930177601 scopus 로고    scopus 로고
    • Cell microenvironment engineering and monitoring for tissue engineering and regenerative medicine: the recent advances
    • Barthes, J., et al. Cell microenvironment engineering and monitoring for tissue engineering and regenerative medicine: the recent advances. BioMed. Res. Int., 2014, 2014, 921905.
    • (2014) BioMed. Res. Int. , vol.2014 , pp. 921905
    • Barthes, J.1
  • 2
    • 84901242248 scopus 로고    scopus 로고
    • Materials as stem cell regulators
    • Murphy, W.L., et al. Materials as stem cell regulators. Nat. Mater. 13 (2014), 547–557.
    • (2014) Nat. Mater. , vol.13 , pp. 547-557
    • Murphy, W.L.1
  • 3
    • 67649920749 scopus 로고    scopus 로고
    • Growth factors, matrices, and forces combine and control stem cells
    • Discher, D.E., et al. Growth factors, matrices, and forces combine and control stem cells. Science 324 (2009), 1673–1677.
    • (2009) Science , vol.324 , pp. 1673-1677
    • Discher, D.E.1
  • 4
    • 38049081273 scopus 로고    scopus 로고
    • Dorland's Medical Dictionary for Health Consumers
    • Saunders
    • Dorland, W.A.N., Dorland's Medical Dictionary for Health Consumers. 2007, Saunders.
    • (2007)
    • Dorland, W.A.N.1
  • 5
    • 84954270816 scopus 로고    scopus 로고
    • Material cues as potent regulators of epigenetics and stem cell function
    • Crowder Spencer, W., et al. Material cues as potent regulators of epigenetics and stem cell function. Cell Stem Cell 18 (2016), 39–52.
    • (2016) Cell Stem Cell , vol.18 , pp. 39-52
    • Crowder Spencer, W.1
  • 6
    • 84924107848 scopus 로고    scopus 로고
    • Cellular responses evoked by different surface characteristics of intraosseous titanium implants
    • Feller, L., et al. Cellular responses evoked by different surface characteristics of intraosseous titanium implants. BioMed. Res. Int., 2015, 2015, 171945.
    • (2015) BioMed. Res. Int. , vol.2015 , pp. 171945
    • Feller, L.1
  • 7
    • 84921654422 scopus 로고    scopus 로고
    • Interplay of matrix stiffness and protein tethering in stem cell differentiation
    • Wen, J.H., et al. Interplay of matrix stiffness and protein tethering in stem cell differentiation. Nat. Mater. 13 (2014), 979–987.
    • (2014) Nat. Mater. , vol.13 , pp. 979-987
    • Wen, J.H.1
  • 8
    • 84923326621 scopus 로고    scopus 로고
    • Substrate stress relaxation regulates cell spreading
    • Chaudhuri, O., et al. Substrate stress relaxation regulates cell spreading. Nat. Commun., 6, 2015, 6364.
    • (2015) Nat. Commun. , vol.6 , pp. 6364
    • Chaudhuri, O.1
  • 9
    • 84880795993 scopus 로고    scopus 로고
    • Role of the extracellular matrix in regulating stem cell fate
    • Watt, F.M., Huck, W.T., Role of the extracellular matrix in regulating stem cell fate. Nat. Rev. Mol. Cell Biol. 14 (2013), 467–473.
    • (2013) Nat. Rev. Mol. Cell Biol. , vol.14 , pp. 467-473
    • Watt, F.M.1    Huck, W.T.2
  • 10
    • 85030438242 scopus 로고    scopus 로고
    • A next generation connectivity map: L1000 Platform and the first 1,000,000 profiles
    • Subramanian, A., et al. A next generation connectivity map: L1000 Platform and the first 1,000,000 profiles. bioRxiv, 2017, 136168.
    • (2017) bioRxiv , pp. 136168
    • Subramanian, A.1
  • 11
    • 84870326718 scopus 로고    scopus 로고
    • Applications of Connectivity Map in drug discovery and development
    • Qu, X.A., Rajpal, D.K., Applications of Connectivity Map in drug discovery and development. Drug Discov. Today 17 (2012), 1289–1298.
    • (2012) Drug Discov. Today , vol.17 , pp. 1289-1298
    • Qu, X.A.1    Rajpal, D.K.2
  • 12
    • 84902203637 scopus 로고    scopus 로고
    • Multiparametric analysis of screening data: growing beyond the single dimension to infinity and beyond
    • Abraham, Y., et al. Multiparametric analysis of screening data: growing beyond the single dimension to infinity and beyond. J. Biomol. Screen. 19 (2014), 628–639.
    • (2014) J. Biomol. Screen. , vol.19 , pp. 628-639
    • Abraham, Y.1
  • 13
    • 84920683698 scopus 로고    scopus 로고
    • Integrating phenotypic small-molecule profiling and human genetics: the next phase in drug discovery
    • Johannessen, C.M., et al. Integrating phenotypic small-molecule profiling and human genetics: the next phase in drug discovery. Trends Genet. 31 (2015), 16–23.
    • (2015) Trends Genet. , vol.31 , pp. 16-23
    • Johannessen, C.M.1
  • 14
    • 84938748113 scopus 로고    scopus 로고
    • Exploring the material-induced transcriptional landscape of osteoblasts on bone graft materials
    • Groen, N., et al. Exploring the material-induced transcriptional landscape of osteoblasts on bone graft materials. Adv. Healthc. Mater. 4 (2015), 1691–1700.
    • (2015) Adv. Healthc. Mater. , vol.4 , pp. 1691-1700
    • Groen, N.1
  • 15
    • 84875829954 scopus 로고    scopus 로고
    • Mapping calcium phosphate activated gene networks as a strategy for targeted osteoinduction of human progenitors in vitro and in vivo
    • Eyckmans, J., et al. Mapping calcium phosphate activated gene networks as a strategy for targeted osteoinduction of human progenitors in vitro and in vivo. Biomaterials 34 (2013), 4612–4621.
    • (2013) Biomaterials , vol.34 , pp. 4612-4621
    • Eyckmans, J.1
  • 16
    • 85007019603 scopus 로고    scopus 로고
    • Linking the transcriptional landscape of bone induction to biomaterial design parameters
    • Groen, N., et al. Linking the transcriptional landscape of bone induction to biomaterial design parameters. Adv. Mater., 29, 2017, 1603259.
    • (2017) Adv. Mater. , vol.29 , pp. 1603259
    • Groen, N.1
  • 17
    • 84962815651 scopus 로고    scopus 로고
    • Applications in image-based profiling of perturbations
    • Caicedo, J.C., et al. Applications in image-based profiling of perturbations. Curr. Opin. Biotechnol. 39 (2016), 134–142.
    • (2016) Curr. Opin. Biotechnol. , vol.39 , pp. 134-142
    • Caicedo, J.C.1
  • 18
    • 85015335626 scopus 로고    scopus 로고
    • Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes
    • Bray, M.-A., et al. Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes. Nat. Protoc. 11 (2016), 1757–1774.
    • (2016) Nat. Protoc. , vol.11 , pp. 1757-1774
    • Bray, M.-A.1
  • 19
    • 84898402897 scopus 로고    scopus 로고
    • Multiplexed ion beam imaging of human breast tumors
    • Angelo, M., et al. Multiplexed ion beam imaging of human breast tumors. Nat. Med. 20 (2014), 436–442.
    • (2014) Nat. Med. , vol.20 , pp. 436-442
    • Angelo, M.1
  • 20
    • 84863208608 scopus 로고    scopus 로고
    • Biological imaging software tools
    • Eliceiri, K.W., et al. Biological imaging software tools. Nat Methods 9 (2012), 697–710.
    • (2012) Nat Methods , vol.9 , pp. 697-710
    • Eliceiri, K.W.1
  • 21
    • 84872784433 scopus 로고    scopus 로고
    • Spheroid culture as a tool for creating 3D complex tissues
    • Fennema, E., et al. Spheroid culture as a tool for creating 3D complex tissues. Trends Biotechnol. 31 (2013), 108–115.
    • (2013) Trends Biotechnol. , vol.31 , pp. 108-115
    • Fennema, E.1
  • 22
    • 77956391258 scopus 로고    scopus 로고
    • Osteoinductive ceramics as a synthetic alternative to autologous bone grafting
    • Yuan, H., et al. Osteoinductive ceramics as a synthetic alternative to autologous bone grafting. Proc. Natl. Acad. Sci. 107 (2010), 13614–13619.
    • (2010) Proc. Natl. Acad. Sci. , vol.107 , pp. 13614-13619
    • Yuan, H.1
  • 23
    • 84904810158 scopus 로고    scopus 로고
    • High throughput assessment and chemometric analysis of the interaction of epithelial and fibroblast cells with a polymer library
    • Celiz, A.D., et al. High throughput assessment and chemometric analysis of the interaction of epithelial and fibroblast cells with a polymer library. Appl. Surf. Sci. 313 (2014), 926–935.
    • (2014) Appl. Surf. Sci. , vol.313 , pp. 926-935
    • Celiz, A.D.1
  • 24
    • 84891904880 scopus 로고    scopus 로고
    • Computational methods in drug discovery
    • Sliwoski, G., et al. Computational methods in drug discovery. Pharmacol. Rev. 66 (2014), 334–395.
    • (2014) Pharmacol. Rev. , vol.66 , pp. 334-395
    • Sliwoski, G.1
  • 25
    • 84971491669 scopus 로고    scopus 로고
    • Creating biomaterials with spatially organized functionality
    • Chow, L.W., Fischer, J.F., Creating biomaterials with spatially organized functionality. Exp. Biol. Med. 241 (2016), 1025–1032, 10.1177/1535370216648023.
    • (2016) Exp. Biol. Med. , vol.241 , pp. 1025-1032
    • Chow, L.W.1    Fischer, J.F.2
  • 26
    • 34748885100 scopus 로고    scopus 로고
    • High throughput surface characterisation of a combinatorial material library
    • Urquhart, A.J., et al. High throughput surface characterisation of a combinatorial material library. Adv. Mater. 19 (2007), 2486–2491.
    • (2007) Adv. Mater. , vol.19 , pp. 2486-2491
    • Urquhart, A.J.1
  • 27
    • 84937801713 scopus 로고    scopus 로고
    • Machine learning: trends, perspectives, and prospects
    • Jordan, M.I., Mitchell, T.M., Machine learning: trends, perspectives, and prospects. Science 349 (2015), 255–260.
    • (2015) Science , vol.349 , pp. 255-260
    • Jordan, M.I.1    Mitchell, T.M.2
  • 28
    • 84930630277 scopus 로고    scopus 로고
    • Deep learning
    • LeCun, Y., et al. Deep learning. Nature 521 (2015), 436–444.
    • (2015) Nature , vol.521 , pp. 436-444
    • LeCun, Y.1
  • 29
    • 0004255908 scopus 로고    scopus 로고
    • Machine Learning
    • McGraw-Hill
    • Mitchell, T.M., Machine Learning. 1997, McGraw-Hill.
    • (1997)
    • Mitchell, T.M.1
  • 30
    • 0003584577 scopus 로고    scopus 로고
    • Artificial Intelligence: A Modern Approach
    • Prentice Hall
    • Russell, S.J., Norvig, P., Artificial Intelligence: A Modern Approach. 2002, Prentice Hall.
    • (2002)
    • Russell, S.J.1    Norvig, P.2
  • 31
    • 0004045406 scopus 로고    scopus 로고
    • Learning Python
    • O'Reilly Media
    • Lutz, M., Learning Python. 2013, O'Reilly Media.
    • (2013)
    • Lutz, M.1
  • 32
    • 84884261877 scopus 로고    scopus 로고
    • Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
    • O'Reilly Media
    • McKinney, W., Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. 2012, O'Reilly Media.
    • (2012)
    • McKinney, W.1
  • 33
    • 84989877003 scopus 로고    scopus 로고
    • R for Data Science
    • O'Reilly
    • Wickham, H., Grolemund, G., R for Data Science. 2016, O'Reilly.
    • (2016)
    • Wickham, H.1    Grolemund, G.2
  • 34
    • 84944034822 scopus 로고    scopus 로고
    • Learning Scikit-Learn: Machine Learning in Python
    • Packt Publishing
    • Garreta, R., Moncecchi, G., Learning Scikit-Learn: Machine Learning in Python. 2013, Packt Publishing.
    • (2013)
    • Garreta, R.1    Moncecchi, G.2
  • 35
    • 56249113343 scopus 로고    scopus 로고
    • Caret package
    • Kuhn, M., Caret package. J. Stat. Softw. 28 (2008), 1–26.
    • (2008) J. Stat. Softw. , vol.28 , pp. 1-26
    • Kuhn, M.1
  • 36
    • 76749092270 scopus 로고    scopus 로고
    • The WEKA data mining software: an update
    • Hall, M., et al. The WEKA data mining software: an update. ACM SIGKDD Explor. Newsl. 11 (2009), 10–18.
    • (2009) ACM SIGKDD Explor. Newsl. , vol.11 , pp. 10-18
    • Hall, M.1
  • 37
  • 38
    • 84866077513 scopus 로고    scopus 로고
    • Combinatorial discovery of polymers resistant to bacterial attachment
    • Hook, A.L., et al. Combinatorial discovery of polymers resistant to bacterial attachment. Nat. Biotechnol. 30 (2012), 868–875.
    • (2012) Nat. Biotechnol. , vol.30 , pp. 868-875
    • Hook, A.L.1
  • 39
    • 84893874008 scopus 로고    scopus 로고
    • An Introduction to Statistical Learning
    • Springer
    • James, G., et al. An Introduction to Statistical Learning. 2013, Springer.
    • (2013)
    • James, G.1
  • 41
    • 84870441792 scopus 로고    scopus 로고
    • Modelling human embryoid body cell adhesion to a combinatorial library of polymer surfaces
    • Epa, V.C., et al. Modelling human embryoid body cell adhesion to a combinatorial library of polymer surfaces. J. Mater. Chem. 22 (2012), 20902–20906.
    • (2012) J. Mater. Chem. , vol.22 , pp. 20902-20906
    • Epa, V.C.1
  • 42
    • 84921798749 scopus 로고    scopus 로고
    • Sparse feature selection methods identify unexpected global cellular response to strontium-containing materials
    • Autefage, H., et al. Sparse feature selection methods identify unexpected global cellular response to strontium-containing materials. Proc. Natl. Acad. Sci. 112 (2015), 4280–4285.
    • (2015) Proc. Natl. Acad. Sci. , vol.112 , pp. 4280-4285
    • Autefage, H.1
  • 43
    • 80053601496 scopus 로고    scopus 로고
    • The determination of stem cell fate by 3D scaffold structures through the control of cell shape
    • Kumar, G., et al. The determination of stem cell fate by 3D scaffold structures through the control of cell shape. Biomaterials 32 (2011), 9188–9196.
    • (2011) Biomaterials , vol.32 , pp. 9188-9196
    • Kumar, G.1
  • 44
    • 84954533026 scopus 로고    scopus 로고
    • Scalable topographies to support proliferation and Oct4 expression by human induced pluripotent stem cells
    • Reimer, A., et al. Scalable topographies to support proliferation and Oct4 expression by human induced pluripotent stem cells. Sci. Rep., 6, 2016, 18948.
    • (2016) Sci. Rep. , vol.6 , pp. 18948
    • Reimer, A.1
  • 45
    • 18244387710 scopus 로고    scopus 로고
    • Review: in vitro, in vivo, in silico: computational systems in tissue engineering and regenerative medicine
    • Semple, J.L., et al. Review: in vitro, in vivo, in silico: computational systems in tissue engineering and regenerative medicine. Tissue Eng. 11 (2005), 341–356.
    • (2005) Tissue Eng. , vol.11 , pp. 341-356
    • Semple, J.L.1
  • 46
    • 84922834072 scopus 로고    scopus 로고
    • Regenerative orthopaedics: in vitro, in vivo… in silico
    • Geris, L., Regenerative orthopaedics: in vitro, in vivo… in silico. Int. Orthop. 38 (2014), 1771–1778.
    • (2014) Int. Orthop. , vol.38 , pp. 1771-1778
    • Geris, L.1
  • 47
    • 84887261735 scopus 로고    scopus 로고
    • Biological networks 101: computational modeling for molecular biologists
    • Scholma, J., et al. Biological networks 101: computational modeling for molecular biologists. Gene 533 (2014), 379–384.
    • (2014) Gene , vol.533 , pp. 379-384
    • Scholma, J.1
  • 48
    • 84930887947 scopus 로고    scopus 로고
    • Abstracting the principles of development using imaging and modeling
    • Xiong, F., Megason, S.G., Abstracting the principles of development using imaging and modeling. Integr. Biol. 7 (2015), 633–642.
    • (2015) Integr. Biol. , vol.7 , pp. 633-642
    • Xiong, F.1    Megason, S.G.2
  • 49
    • 84952638889 scopus 로고    scopus 로고
    • How computational models can help unlock biological systems
    • Brodland, G.W., How computational models can help unlock biological systems. Semin. Cell Dev. Biol. 00 (2015), 62–73.
    • (2015) Semin. Cell Dev. Biol. , pp. 62-73
    • Brodland, G.W.1
  • 50
    • 84877994136 scopus 로고    scopus 로고
    • New development in FreeFem++
    • Hecht, F., New development in FreeFem++. J. Numer. Math. 20 (2012), 251–266.
    • (2012) J. Numer. Math. , vol.20 , pp. 251-266
    • Hecht, F.1
  • 51
    • 85030446431 scopus 로고    scopus 로고
    • SBML and synthetic biology
    • Published online September 6, 2011.
    • Myers, C., SBML and synthetic biology. Nat. Preceed., 2011, 10.1038/npre.2011.6343.1 Published online September 6, 2011.
    • (2011) Nat. Preceed.
    • Myers, C.1
  • 52
    • 84982169062 scopus 로고    scopus 로고
    • The CellML metadata framework 2.0 specification
    • Cooling, M.T., Hunter, P., The CellML metadata framework 2.0 specification. J. Integr. Bioinform. 12 (2015), 86–103.
    • (2015) J. Integr. Bioinform. , vol.12 , pp. 86-103
    • Cooling, M.T.1    Hunter, P.2
  • 53
    • 85178122976 scopus 로고    scopus 로고
    • A Guide to MATLAB: For Beginners and Experienced Users
    • Cambridge University Press
    • Hunt, B.R., et al. A Guide to MATLAB: For Beginners and Experienced Users. 2014, Cambridge University Press.
    • (2014)
    • Hunt, B.R.1
  • 54
    • 84882758675 scopus 로고    scopus 로고
    • Programming biological models in Python using PySB
    • Lopez, C.F., et al. Programming biological models in Python using PySB. Mol. Syst. Biol., 9, 2013, 646.
    • (2013) Mol. Syst. Biol. , vol.9 , pp. 646
    • Lopez, C.F.1
  • 55
    • 0035478586 scopus 로고    scopus 로고
    • The Virtual Cell: a software environment for computational cell biology
    • Loew, L.M., Schaff, J.C., The Virtual Cell: a software environment for computational cell biology. Trends Biotechnol. 19 (2001), 401–406.
    • (2001) Trends Biotechnol. , vol.19 , pp. 401-406
    • Loew, L.M.1    Schaff, J.C.2
  • 56
    • 84859314755 scopus 로고    scopus 로고
    • Multi-scale modeling of tissues using CompuCell3D
    • Swat, M.H., et al. Multi-scale modeling of tissues using CompuCell3D. Methods Cell Biol., 110, 2012, 325.
    • (2012) Methods Cell Biol. , vol.110 , pp. 325
    • Swat, M.H.1
  • 57
    • 84893596337 scopus 로고    scopus 로고
    • Morpheus: a user-friendly modeling environment for multiscale and multicellular systems biology
    • Starruß, J., et al. Morpheus: a user-friendly modeling environment for multiscale and multicellular systems biology. Bioinformatics 30 (2014), 1331–1332.
    • (2014) Bioinformatics , vol.30 , pp. 1331-1332
    • Starruß, J.1
  • 58
    • 84859909916 scopus 로고    scopus 로고
    • FEBio: finite elements for biomechanics
    • Maas, S.A., et al. FEBio: finite elements for biomechanics. J. Biomech. Eng., 134, 2012, 011005.
    • (2012) J. Biomech. Eng. , vol.134 , pp. 011005
    • Maas, S.A.1
  • 59
    • 0030956033 scopus 로고    scopus 로고
    • Single-particle tracking: applications to membrane dynamics
    • Saxton, M.J., Jacobson, K., Single-particle tracking: applications to membrane dynamics. Annu. Rev. Biophys. Biomol. Struct. 26 (1997), 373–399.
    • (1997) Annu. Rev. Biophys. Biomol. Struct. , vol.26 , pp. 373-399
    • Saxton, M.J.1    Jacobson, K.2
  • 60
    • 85030420076 scopus 로고    scopus 로고
    • Theoretical understanding of bio-interfaces/bio-surfaces by simulation: a mini review
    • Tang, Y.H., Zhang, H.P., Theoretical understanding of bio-interfaces/bio-surfaces by simulation: a mini review. Biosurf. Biotribol. 2 (2016), 151–161.
    • (2016) Biosurf. Biotribol. , vol.2 , pp. 151-161
    • Tang, Y.H.1    Zhang, H.P.2
  • 61
    • 84923354599 scopus 로고    scopus 로고
    • Consequences of chirality on the dynamics of a water-soluble supramolecular polymer
    • Baker, M.B., et al. Consequences of chirality on the dynamics of a water-soluble supramolecular polymer. Nat. Commun., 6, 2015, 6234.
    • (2015) Nat. Commun. , vol.6 , pp. 6234
    • Baker, M.B.1
  • 62
    • 84896548221 scopus 로고    scopus 로고
    • Current trends in the design of scaffolds for computer-aided tissue engineering
    • Giannitelli, S.M., et al. Current trends in the design of scaffolds for computer-aided tissue engineering. Acta Biomater. 10 (2014), 580–594.
    • (2014) Acta Biomater. , vol.10 , pp. 580-594
    • Giannitelli, S.M.1
  • 63
    • 35348975035 scopus 로고    scopus 로고
    • Simulation of tissue differentiation in a scaffold as a function of porosity, Young's modulus and dissolution rate: application of mechanobiological models in tissue engineering
    • Byrne, D.P., et al. Simulation of tissue differentiation in a scaffold as a function of porosity, Young's modulus and dissolution rate: application of mechanobiological models in tissue engineering. Biomaterials 28 (2007), 5544–5554.
    • (2007) Biomaterials , vol.28 , pp. 5544-5554
    • Byrne, D.P.1
  • 64
    • 33646017698 scopus 로고    scopus 로고
    • Framework for optimal design of porous scaffold microstructure by computational simulation of bone regeneration
    • Adachi, T., et al. Framework for optimal design of porous scaffold microstructure by computational simulation of bone regeneration. Biomaterials 27 (2006), 3964–3972.
    • (2006) Biomaterials , vol.27 , pp. 3964-3972
    • Adachi, T.1
  • 65
    • 84963726737 scopus 로고    scopus 로고
    • Computational modeling of phagocyte transmigration for foreign body responses to subcutaneous biomaterial implants in mice
    • Kang, M., et al. Computational modeling of phagocyte transmigration for foreign body responses to subcutaneous biomaterial implants in mice. BMC Bioinform., 17, 2016, 111.
    • (2016) BMC Bioinform. , vol.17 , pp. 111
    • Kang, M.1
  • 66
    • 80052267007 scopus 로고    scopus 로고
    • Designing optimal calcium phosphate scaffold–cell combinations using an integrative model-based approach
    • Carlier, A., et al. Designing optimal calcium phosphate scaffold–cell combinations using an integrative model-based approach. Acta Biomater. 7 (2011), 3573–3585.
    • (2011) Acta Biomater. , vol.7 , pp. 3573-3585
    • Carlier, A.1
  • 67
    • 84988416877 scopus 로고    scopus 로고
    • Computational modelling of local calcium ions release from calcium phosphate-based scaffolds
    • Manhas, V., et al. Computational modelling of local calcium ions release from calcium phosphate-based scaffolds. Biomech. Model. Mechanobiol. 16 (2017), 425–438.
    • (2017) Biomech. Model. Mechanobiol. , vol.16 , pp. 425-438
    • Manhas, V.1
  • 68
    • 85003723280 scopus 로고    scopus 로고
    • Imagining the future of bioimage analysis
    • Meijering, E., et al. Imagining the future of bioimage analysis. Nat. Biotechnol. 34 (2016), 1250–1255.
    • (2016) Nat. Biotechnol. , vol.34 , pp. 1250-1255
    • Meijering, E.1
  • 69
    • 0036081355 scopus 로고    scopus 로고
    • Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
    • Edgar, R., et al. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 30 (2002), 207–210.
    • (2002) Nucleic Acids Res. , vol.30 , pp. 207-210
    • Edgar, R.1
  • 70
    • 85030420377 scopus 로고    scopus 로고
    • The Image Data Resource: a scalable platform for biological image data access, integration, and dissemination
    • Williams, E., et al. The Image Data Resource: a scalable platform for biological image data access, integration, and dissemination. bioRxiv, 2016, 089359.
    • (2016) bioRxiv , pp. 089359
    • Williams, E.1
  • 71
    • 85030436715 scopus 로고    scopus 로고
    • I tried a bunch of things: the dangers of unexpected overfitting in classification
    • Skocik, M., et al. I tried a bunch of things: the dangers of unexpected overfitting in classification. bioRxiv, 2016, 078816.
    • (2016) bioRxiv , pp. 078816
    • Skocik, M.1
  • 72
    • 85027232137 scopus 로고    scopus 로고
    • Voodoo machine learning for clinical predictions
    • Saeb, S., et al. Voodoo machine learning for clinical predictions. bioRxiv, 2016, 059774.
    • (2016) bioRxiv , pp. 059774
    • Saeb, S.1
  • 73
    • 0004055894 scopus 로고    scopus 로고
    • Convex Optimization
    • Cambridge University Press
    • Boyd, S., Vandenberghe, L., Convex Optimization. 2004, Cambridge University Press.
    • (2004)
    • Boyd, S.1    Vandenberghe, L.2
  • 74
    • 85101445097 scopus 로고    scopus 로고
    • Applied Regression Analysis
    • John Wiley & Sons
    • Draper, N.R., Smith, H., Applied Regression Analysis. 2014, John Wiley & Sons.
    • (2014)
    • Draper, N.R.1    Smith, H.2
  • 75
    • 84893405732 scopus 로고    scopus 로고
    • Data clustering: a review
    • Jain, A.K., et al. Data clustering: a review. ACM Comput. Surv. 31 (1999), 264–323.
    • (1999) ACM Comput. Surv. , vol.31 , pp. 264-323
    • Jain, A.K.1
  • 76
    • 78650121315 scopus 로고    scopus 로고
    • Clustering algorithms in biomedical research: a review
    • Xu, R., Wunsch, D.C. 2nd, Clustering algorithms in biomedical research: a review. IEEE Rev. Biomed. Eng. 3 (2010), 120–154.
    • (2010) IEEE Rev. Biomed. Eng. , vol.3 , pp. 120-154
    • Xu, R.1    Wunsch, D.C.2
  • 77
    • 0003946510 scopus 로고    scopus 로고
    • Principal Component Analysis
    • Springer New York
    • Jolliffe, I.T., Principal Component Analysis. 2013, Springer New York.
    • (2013)
    • Jolliffe, I.T.1
  • 78
    • 33745561205 scopus 로고    scopus 로고
    • An introduction to variable and feature selection
    • Guyon, I., et al. An introduction to variable and feature selection. J. Mach. Learn. Res. 3 (2003), 1157–1182.
    • (2003) J. Mach. Learn. Res. , vol.3 , pp. 1157-1182
    • Guyon, I.1
  • 79
    • 38349018685 scopus 로고    scopus 로고
    • Dimensionality Reduction: a Comparative Review
    • Tilburg University Report No.: 2009–005. Published online October 29, 2009.
    • Van Der Maaten, L., et al. Dimensionality Reduction: a Comparative Review., 2009, Tilburg University Report No.: 2009–005. Published online October 29, 2009. https://www.tilburguniversity.edu/upload/59afb3b8-21a5-4c78-8eb3-6510597382db_TR2009005.pdf.
    • (2009)
    • Van Der Maaten, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.