{"id":"https://openalex.org/W6967708570","doi":"https://doi.org/10.5281/zenodo.13343727","title":"MD simulations files for: Enhanced Sampling of Biomolecular Slow Conformational Transitions Using Adaptive Sampling and Machine Learning","display_name":"MD simulations files for: Enhanced Sampling of Biomolecular Slow Conformational Transitions Using Adaptive Sampling and Machine Learning","publication_year":2024,"publication_date":"2024-08-19","ids":{"openalex":"https://openalex.org/W6967708570","doi":"https://doi.org/10.5281/zenodo.13343727"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.13343727","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.13343727","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.13343727","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Wang, Yong","orcid":"https://orcid.org/0000-0001-9156-0377"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang, Yong","raw_affiliation_strings":["Zhejiang University"],"raw_orcid":"https://orcid.org/0000-0001-9156-0377","affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zhang, Mingyuan","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang, Mingyuan","raw_affiliation_strings":["Zhejiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/replicate","display_name":"Replicate","score":0.7260000109672546},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6840000152587891},{"id":"https://openalex.org/keywords/scripting-language","display_name":"Scripting language","score":0.6230000257492065},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5936999917030334},{"id":"https://openalex.org/keywords/adaptive-sampling","display_name":"Adaptive sampling","score":0.5845000147819519},{"id":"https://openalex.org/keywords/directory","display_name":"Directory","score":0.4413999915122986}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.762499988079071},{"id":"https://openalex.org/C2781162219","wikidata":"https://www.wikidata.org/wiki/Q26250693","display_name":"Replicate","level":2,"score":0.7260000109672546},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6840000152587891},{"id":"https://openalex.org/C61423126","wikidata":"https://www.wikidata.org/wiki/Q187432","display_name":"Scripting language","level":2,"score":0.6230000257492065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6151000261306763},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5936999917030334},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.5845000147819519},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5328999757766724},{"id":"https://openalex.org/C2777683733","wikidata":"https://www.wikidata.org/wiki/Q201456","display_name":"Directory","level":2,"score":0.4413999915122986},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40709999203681946},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.40560001134872437},{"id":"https://openalex.org/C2777936996","wikidata":"https://www.wikidata.org/wiki/Q17148461","display_name":"Conformational ensembles","level":3,"score":0.31450000405311584},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.313400000333786},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2856999933719635},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.2639000117778778}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5281/zenodo.13343727","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.13343727","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"doi:10.5281/zenodo.13343727","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.13343727","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Here's":[0],"a":[1,406,414,564],"rephrased":[2],"version":[3],"of":[4,11,40,70,99],"the":[5,32,36,68,85,92,100,116,132,143,179,183,198,202,212,217,235,252,263,289,307,325,329,355,382,399,437,481,561,581],"README":[6],"file:":[7],"####":[8],"Enhanced":[9],"Sampling":[10,18,39,47,486],"Biomolecular":[12,41],"Slow":[13,42],"Conformational":[14,43],"Transitions":[15,44],"Using":[16,45],"Adaptive":[17,46],"and":[19,48,56,80,87,95,108,174,185,191,229,279,316,367,385,413,471,475,559],"Machine":[20,49],"Learning":[21],"**Authors:**":[22],"Mingyuan":[23,52],"Zhang,":[24,53],"Hao":[25,54],"Wu,":[26,55],"Yong":[27,57],"Wang":[28],"This":[29,162,498,522],"repository":[30],"contains":[31,500,524],"official":[33],"implementation":[34,163,582],"for":[35,134,261,305,354,364,398,410,418,446,454,489,515,530,541,548],"paper":[37,103],"\"Enhanced":[38],"Learning\"":[50],"by":[51,588],"Wang.":[58],"Included":[59],"are":[60,172,176,222,240,449,469,494,518,555],"all":[61,77,115,169,296,314,335,345,378,394,427,466,504,536],"trajectories":[62,493],"from":[63,216,338,381,430],"our":[64,124,593],"MD":[65],"simulations":[66],"in":[67,90,142,160,224,360,373,402,462,496,520],"form":[69],"PLUMED":[71,395,411],"COLVAR":[72,336],"files,":[73],"as":[74,76,120,146,451],"well":[75],"analysis":[78,317],"scripts":[79,209,501,514,525],"files":[81,119,246,274,298,321,337,346,397,429,538],"needed":[82],"to":[83,166,194,210,287,323,328,348,435,502,507,526,557,573,580],"replicate":[84,201,211,324,503,527],"results":[86,213],"figures":[88,215,370,380,505,528],"presented":[89],"both":[91,135],"main":[93,218,237,383],"text":[94,219,384],"Supporting":[96],"Information":[97,553],"(SI)":[98],"paper.":[101],"The":[102,128,156,208,282,362],"features":[104],"two":[105],"examples:":[106],"Ala2":[107],"Ala10.":[109],"For":[110],"each,":[111],"we":[112,138],"have":[113],"organized":[114,223],"associated":[117],"simulation":[118,126,265,291,309,315,537],"they":[121],"were":[122,433],"during":[123,248,276],"automated":[125,264,290,308,330],"pipeline.":[127,204,331],"directory":[129],"structure":[130],"is":[131,158,164,259,285,303,371,566],"same":[133],"examples.":[136],"Here,":[137],"use":[139,167],"Ala2,":[140],"found":[141,359,495],"`Ala2`":[144,236],"folder,":[145],"an":[147,542,590],"example:":[148],"###":[149,231,551],"Key":[150],"Components":[151],"-":[152,205,243,267,293,311,533],"**Automated":[153,458],"Pipeline":[154,459],"Implementation:**":[155],"pipeline":[157],"implemented":[159],"`Ala2/7-adaptive-40ps/ala2.ipynb`.":[161],"ready":[165],"once":[168],"required":[170,286,322],"packages":[171,468],"installed,":[173],"gmx/gmx_mpi/plumed":[175],"callable":[177],"within":[178,480],"notebook.":[180,483],"After":[181],"configuring":[182],"environment":[184],"specifying":[186],"parameters":[187],"like":[188],"`gpu_id`,":[189],"`ntomp`,":[190],"`n_sim`":[192],"according":[193],"your":[195],"hardware,":[196],"running":[197,262,306],"blocks":[199],"will":[200],"entire":[203],"**Analysis":[206],"Scripts:**":[207],"or":[214,220,587],"SI":[221],"three":[225],"files:":[226],"`Ala2/7-adaptive-40ps/AdaptiveSamplingAnalysis.ipynb`,":[227],"`Ala2/7-adaptive-40ps/compare_with_msm.ipynb`,":[228],"`Ala2/7-adaptive-40ps/opes/COLVAR/analysis.ipynb`.":[230,374],"Directory":[232],"Structure":[233],"Under":[234],"directory,":[238],"there":[239],"seven":[241],"subdirectories:":[242],"**`Ala2/1-topol/`**:":[244],"Contains":[245,295,313,344,535],"generated":[247,275],"system":[249],"construction,":[250],"including":[251,300,351],"final":[253,356],"Gromacs":[254],"topology":[255,407,415],"file":[256,284,408,416],"`topol.top`,":[257],"which":[258,302],"necessary":[260,304,453],"script.":[266,292,310],"**`Ala2/2-em/`,":[268],"`Ala2/3-nvt/`,":[269],"`Ala2/4-npt/`**:":[270],"These":[271],"directories":[272],"store":[273],"energy":[277],"minimization":[278],"NVT/NPT":[280],"equilibration.":[281],"`Ala2/4-npt/npt.gro`":[283],"run":[288],"**`Ala2/mdp/`**:":[294],"mdp":[297],"used,":[299],"`Ala2/mdp/md_detail.mdp`,":[301],"**`Ala2/7-adaptive-40ps/`**:":[312],"scripts,":[318],"along":[319],"with":[320,576],"study":[326],"related":[327,347,506,579],"1.":[332],"**`Ala2/7-adaptive-40ps/CV/`**:":[333],"Stores":[334,393],"adaptive":[339,403,420,431,491,508,544],"sampling":[340,404,421,432,492,545],"simulations.":[341],"2.":[342],"**`Ala2/7-adaptive-40ps/opes/`**:":[343],"OPES":[349,366],"simulations,":[350,405],"raw":[352],"data":[353],"FES":[357,368],"plots":[358],"`Ala2/7-adaptive-40ps/opes/COLVAR/`.":[361],"script":[363],"replicating":[365],"estimation":[369],"located":[372,519],"3.":[375],"**`Ala2/7-adaptive-40ps/figures/`**:":[376],"Includes":[377],"original":[379],"SI,":[386],"saved":[387],"at":[388,585],"600":[389],"dpi.":[390],"4.":[391],"**`Ala2/7-adaptive-40ps/traj_and_dat/`**:":[392],"`*.dat`":[396],"`DRIVER`":[400],"utility":[401],"`input.pdb`":[409],"`MOLINFO`,":[412],"`seed_ref.pdb`":[417],"MDAnalysis":[419],"seed":[422],"`*.gro`":[423],"generation.":[424],"Note":[425],"that":[426,465],"`*.xtc`":[428],"deleted":[434],"reduce":[436],"package":[438],"size.":[439],"5.":[440],"**Seed":[441],"Index":[442],"Files:**":[443],"Seed":[444],"indices":[445],"each":[447],"round":[448],"stored":[450],"`Ala2/7-adaptive-40ps/round{i}_seed.txt`,":[452],"figure":[455],"replication.":[456],"6.":[457],"Notebook:**":[460],"Implemented":[461],"`Ala2/ala2.ipynb`.":[463],"Ensure":[464],"imported":[467],"installed":[470],"gromacs":[472],"(both":[473],"gmx":[474],"gmx_mpi)/plumed":[476],"can":[477],"be":[478],"called":[479],"Jupyter":[482],"7.":[484],"**Adaptive":[485],"Analysis:**":[487],"Scripts":[488],"analyzing":[490],"`Ala2/AdaptiveSamplingAnalysis.ipynb`.":[497],"notebook":[499,523],"sampling.":[509],"8.":[510],"**MSM":[511],"Comparison:**":[512],"Analysis":[513],"MSM":[516,549],"comparison":[517],"`Ala2/compare_with_msm.ipynb`.":[521],"used":[529],"MSM/OPES":[531],"comparison.":[532,550],"**`Ala2/8-adaptive-400ps/`**:":[534],"(except":[539],"xtc)":[540],"additional":[543],"dataset":[546],"computed":[547],"Contact":[552],"We":[554],"continuing":[556],"test":[558],"improve":[560],"pipeline,":[562],"so":[563],"tutorial":[565],"not":[567],"yet":[568],"available.":[569],"Please":[570],"feel":[571],"free":[572],"reach":[574],"out":[575],"any":[577],"questions":[578],"via":[583],"email":[584],"mingyuanzhang@zju.edu.cn":[586],"raising":[589],"issue":[591],"on":[592],"GitHub":[594],"page:":[595],"https://github.com/yongwangCPH/papers/tree/main/2024/ALICE.":[596]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}