The ugly, bad, and good stories of large-scale biomolecular simulations
Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranou...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Gupta, Chitrak [verfasserIn] |
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E-Artikel |
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| Sprache: |
Englisch |
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2022transfer abstract |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Coprocessing of Stainless-Steel Pickling Sludge with Laterite Ore via Rotary Kiln-Electric Furnace Route: Enhanced Desulfurization and Metal Recovery - Li, Guanghui ELSEVIER, 2020, review of all advances : evaluation of key references : comprehensive listing of papers, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:73 ; year:2022 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.sbi.2022.102338 |
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ELV057181128 |
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| 520 | |a Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations. | ||
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10.1016/j.sbi.2022.102338 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001712.pica (DE-627)ELV057181128 (ELSEVIER)S0959-440X(22)00011-2 DE-627 ger DE-627 rakwb eng 660 540 333.7 VZ 58.18 bkl Gupta, Chitrak verfasserin aut The ugly, bad, and good stories of large-scale biomolecular simulations 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations. Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations. CG Elsevier ns Elsevier ms Elsevier MD Elsevier μs Elsevier fs Elsevier Sarkar, Daipayan oth Tieleman, D. Peter oth Singharoy, Abhishek oth Enthalten in Elsevier Li, Guanghui ELSEVIER Coprocessing of Stainless-Steel Pickling Sludge with Laterite Ore via Rotary Kiln-Electric Furnace Route: Enhanced Desulfurization and Metal Recovery 2020 review of all advances : evaluation of key references : comprehensive listing of papers Amsterdam [u.a.] (DE-627)ELV004786408 volume:73 year:2022 pages:0 https://doi.org/10.1016/j.sbi.2022.102338 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 58.18 Chemische Betriebstechnik VZ AR 73 2022 0 |
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10.1016/j.sbi.2022.102338 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001712.pica (DE-627)ELV057181128 (ELSEVIER)S0959-440X(22)00011-2 DE-627 ger DE-627 rakwb eng 660 540 333.7 VZ 58.18 bkl Gupta, Chitrak verfasserin aut The ugly, bad, and good stories of large-scale biomolecular simulations 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations. Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations. CG Elsevier ns Elsevier ms Elsevier MD Elsevier μs Elsevier fs Elsevier Sarkar, Daipayan oth Tieleman, D. Peter oth Singharoy, Abhishek oth Enthalten in Elsevier Li, Guanghui ELSEVIER Coprocessing of Stainless-Steel Pickling Sludge with Laterite Ore via Rotary Kiln-Electric Furnace Route: Enhanced Desulfurization and Metal Recovery 2020 review of all advances : evaluation of key references : comprehensive listing of papers Amsterdam [u.a.] (DE-627)ELV004786408 volume:73 year:2022 pages:0 https://doi.org/10.1016/j.sbi.2022.102338 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 58.18 Chemische Betriebstechnik VZ AR 73 2022 0 |
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10.1016/j.sbi.2022.102338 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001712.pica (DE-627)ELV057181128 (ELSEVIER)S0959-440X(22)00011-2 DE-627 ger DE-627 rakwb eng 660 540 333.7 VZ 58.18 bkl Gupta, Chitrak verfasserin aut The ugly, bad, and good stories of large-scale biomolecular simulations 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations. Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations. CG Elsevier ns Elsevier ms Elsevier MD Elsevier μs Elsevier fs Elsevier Sarkar, Daipayan oth Tieleman, D. Peter oth Singharoy, Abhishek oth Enthalten in Elsevier Li, Guanghui ELSEVIER Coprocessing of Stainless-Steel Pickling Sludge with Laterite Ore via Rotary Kiln-Electric Furnace Route: Enhanced Desulfurization and Metal Recovery 2020 review of all advances : evaluation of key references : comprehensive listing of papers Amsterdam [u.a.] (DE-627)ELV004786408 volume:73 year:2022 pages:0 https://doi.org/10.1016/j.sbi.2022.102338 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 58.18 Chemische Betriebstechnik VZ AR 73 2022 0 |
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10.1016/j.sbi.2022.102338 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001712.pica (DE-627)ELV057181128 (ELSEVIER)S0959-440X(22)00011-2 DE-627 ger DE-627 rakwb eng 660 540 333.7 VZ 58.18 bkl Gupta, Chitrak verfasserin aut The ugly, bad, and good stories of large-scale biomolecular simulations 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations. Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations. CG Elsevier ns Elsevier ms Elsevier MD Elsevier μs Elsevier fs Elsevier Sarkar, Daipayan oth Tieleman, D. Peter oth Singharoy, Abhishek oth Enthalten in Elsevier Li, Guanghui ELSEVIER Coprocessing of Stainless-Steel Pickling Sludge with Laterite Ore via Rotary Kiln-Electric Furnace Route: Enhanced Desulfurization and Metal Recovery 2020 review of all advances : evaluation of key references : comprehensive listing of papers Amsterdam [u.a.] (DE-627)ELV004786408 volume:73 year:2022 pages:0 https://doi.org/10.1016/j.sbi.2022.102338 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 58.18 Chemische Betriebstechnik VZ AR 73 2022 0 |
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Coprocessing of Stainless-Steel Pickling Sludge with Laterite Ore via Rotary Kiln-Electric Furnace Route: Enhanced Desulfurization and Metal Recovery |
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Coprocessing of Stainless-Steel Pickling Sludge with Laterite Ore via Rotary Kiln-Electric Furnace Route: Enhanced Desulfurization and Metal Recovery |
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The ugly, bad, and good stories of large-scale biomolecular simulations |
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The ugly, bad, and good stories of large-scale biomolecular simulations |
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Gupta, Chitrak |
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Coprocessing of Stainless-Steel Pickling Sludge with Laterite Ore via Rotary Kiln-Electric Furnace Route: Enhanced Desulfurization and Metal Recovery |
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Coprocessing of Stainless-Steel Pickling Sludge with Laterite Ore via Rotary Kiln-Electric Furnace Route: Enhanced Desulfurization and Metal Recovery |
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10.1016/j.sbi.2022.102338 |
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ugly, bad, and good stories of large-scale biomolecular simulations |
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The ugly, bad, and good stories of large-scale biomolecular simulations |
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Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations. |
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Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations. |
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Molecular modeling of large biomolecular assemblies exemplifies a disruptive area holding both promises and contentions. Propelled by peta and exascale computing, several simulation methodologies have now matured into user-friendly tools that are successfully employed for modeling viruses, membranous nano-constructs, and key pieces of the genetic machinery. We present three unifying biophysical themes that emanate from some of the most recent multi-million atom simulation endeavors. Despite connecting molecular changes with phenotypic outcomes, the quality measures of these simulations remain questionable. We discuss the existing and upcoming strategies for constructing representative ensembles of large systems, how new computing technologies will boost this area, and make a point that integrative modeling guided by experimental data is the future of biomolecular computations. |
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The ugly, bad, and good stories of large-scale biomolecular simulations |
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Sarkar, Daipayan Tieleman, D. Peter Singharoy, Abhishek |
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