{"id":12130,"date":"2021-01-13T09:30:00","date_gmt":"2021-01-13T11:30:00","guid":{"rendered":"https:\/\/mindthegraph.com\/blog\/?p=12130"},"modified":"2022-10-18T08:09:26","modified_gmt":"2022-10-18T11:09:26","slug":"pyscratch-spatial-and-temporal-information-from-scratch-assays","status":"publish","type":"post","link":"https:\/\/mindthegraph.com\/blog\/da\/pyscratch-spatial-og-temporal-information-fra-scratch-assays\/","title":{"rendered":"PyScratch: Et nyt v\u00e6rkt\u00f8j til at behandle rumlig og tidsm\u00e6ssig information fra Scratch Assays"},"content":{"rendered":"

PyScratch er en ny open source-software implementeret i Python til analyse af migrationsdata, med en brugervenlig gr\u00e6nseflade, der g\u00f8r det muligt for forskere med f\u00e5 eller ingen programmeringsf\u00e6rdigheder at bruge det. <\/p>\n\n\n\n

Softwaren blev udviklet i et samarbejde mellem tre brasilianske forskere i NanoCell Interactions-laboratoriet p\u00e5 University of Campinas i 2017. <\/p>\n\n\n\n

Det blev f\u00f8dt af disse forskeres behov, og i dag er softwarens form\u00e5l at lette forskernes daglige praksis, udelukke den manuelle analyse, \u00f8ge reproducerbarheden og minimere menneskelige fejl.<\/p>\n\n\n\n

\"\"<\/a><\/figure><\/div>\n\n\n\n

Billedanalyse har v\u00e6ret en af de vigtigste metoder, som forskere har brugt til at analysere resultater. <\/p>\n\n\n\n

Ikke kun brugen af automatiserede mikroskoper er steget i de seneste \u00e5r, men ogs\u00e5 kompleksiteten af de indsamlede data. <\/p>\n\n\n\n

En del af en forskers job er at finde ud af, hvordan man h\u00e5ndterer en ny slags information, og derudover analysere og behandle data. <\/p>\n\n\n\n

For at det kan ske, har forskerne brug for gode og specialiserede v\u00e6rkt\u00f8jer til at udtr\u00e6kke og fortolke alle data korrekt.<\/p>\n\n\n\n

PyScratch blev f\u00f8rst skabt for at hj\u00e6lpe Fernanda Garcia-Fossa, en biologisk forsker, med at analysere en enorm m\u00e6ngde data fra hendes migrationsassays. <\/p>\n\n\n\n

\"Jeg kradsede kr\u00e6ftcellerne op og inkuberede dem i udstyret i 48 timer, mens jeg tog billeder hvert 15. minut, og efter kun \u00e9t eksperiment havde jeg omkring tusind billeder at se p\u00e5 og analysere! <\/p>\n\n\n\n

Det var umuligt at g\u00f8re det manuelt\", siger Garcia-Fossa. For at l\u00f8se det problem gik Garcia-Fossa til sin partner, fysikeren Vladimir Gaal, for at f\u00e5 hj\u00e6lp. P\u00e5 det tidspunkt var Gaal ved at l\u00e6re Python, hvilket var en fantastisk mulighed for at bruge den viden i praksis.<\/p>\n\n\n\n

S\u00e5 de arbejdede begge med l\u00f8sningen gennem en Python-rutine, som genkendte de ridsede omr\u00e5der og eksporterede dem til en csv-fil. <\/p>\n\n\n\n

\"Med tiden f\u00f8lte vi, at det var n\u00f8dvendigt at udvikle en brugergr\u00e6nseflade, der gjorde det endnu lettere at bruge, s\u00e5 vi ogs\u00e5 kunne udgive softwaren til enhver forsker, der havde brug for at bruge den,\" siger Garcia-Fossa om softwareartiklen, som du kan tjekke ud. klik her<\/a>.<\/p>\n\n\n\n

Garcia-Fossa fort\u00e6ller ogs\u00e5, at det tog et stykke tid at genkende og definere migrationsomr\u00e5det ud fra billederne, da billederne kan v\u00e6re meget forskellige fra hinanden p\u00e5 grund af lys, fokus og kontrast, og den version, der bruges i dag, kan allerede analysere ret godt. <\/p>\n\n\n\n

Ikke desto mindre arbejder de stadig p\u00e5 softwaren og lancerer nye og bedre versioner, da den offentliggjorte artikel har bragt nogle forbedringsbehov op p\u00e5 grund af brugernes eftersp\u00f8rgsel.<\/p>\n\n\n\n

Det assay, der bruges til at validere softwarens ydeevne, migrationsassayet, scratch assayet eller s\u00e5rheling, er et assay, der ofte bruges i biologi, fordi det g\u00f8r det muligt at analysere den underliggende mekanisme for fysiologiske og patologiske cellul\u00e6re h\u00e6ndelser. <\/p>\n\n\n\n

At studere s\u00e5rheling er en vigtig m\u00e5de at forst\u00e5 udvikling og v\u00e6vsmodellering p\u00e5, foruden angiogenese og tumorudvikling. <\/p>\n\n\n\n

N\u00e5r assayet udf\u00f8res i to dimensioner, er det muligt at m\u00e5le, hvor hurtigt cellerne reagerer p\u00e5 s\u00e5ret og d\u00e6kker det definerede omr\u00e5de.<\/p>\n\n\n\n

Med andre ord er eksperimentet grundl\u00e6ggende at skabe et hul i monolaget af konfluente celler i en plak. <\/p>\n\n\n\n

Over tid begynder cellerne at migrere for at fylde hullet, og hastigheden af cellernes migration kan m\u00e5les. <\/p>\n\n\n\n

For at m\u00e5le cellemigrationshastigheden er de n\u00f8dt til at tage en masse billeder, hvilket igen er et problematisk trin i analysen, fordi det kr\u00e6ver manuel m\u00e5ling. <\/p>\n\n\n\n

Heldigvis har vi i dag en masse teknologi til r\u00e5dighed, som kan forbedre og opgradere vores analysepipeline, s\u00e5 forskerne kan anvende bedre og mere personlige metoder til at opn\u00e5 et resultat. <\/p>\n\n\n\n

Ligesom Garcia-Fossa og Gaal gjorde det.<\/p>\n\n\n\n

I dag er det muligt at finde andre kommercielle og ikke-kommercielle v\u00e6rkt\u00f8jer til behandling af s\u00e5romr\u00e5det. <\/p>\n\n\n\n

Men de er ikke s\u00e5 enkle som PyScratch, og de kr\u00e6ver en vis grad af programmering af brugeren og kr\u00e6ver ogs\u00e5 fuldtids opm\u00e6rksomhed fra brugeren, hvilket g\u00f8r analysen mere modtagelig for menneskelige fejl, plus den tid, det tager forskeren at analysere alle billeder og data.<\/p>\n\n\n\n

I artiklen forklarer forfatterne, hvordan softwaren fungerer. Fra alle de billeder, der blev taget i eksperimentet, f\u00e5r brugeren en fil med kommaseparerede v\u00e6rdier (.cvs), et output, der gemmer tabeldata i ren tekst. <\/p>\n\n\n\n

Brugeren kan derefter behandle dataene i sin s\u00e6dvanlige rutine. Garcia-Fossa siger, at programmet var afg\u00f8rende for hendes speciale: \"Softwaren omdanner inputdata til v\u00e6rdier, der giver biologisk mening, som f.eks. cellemigrationshastighed. <\/p>\n\n\n\n

Jeg kunne bedre analysere effekten af min nanopartikel p\u00e5 prostatacancerceller og m\u00e5le cellernes migrationshastighed og det n\u00f8jagtige tidspunkt for den gode lukning, alt sammen takket v\u00e6re PyScratch.\"<\/p>\n\n\n\n

\"\"<\/a><\/figure><\/div>\n\n\n\n

Hvis du vil pr\u00f8ve PyScratch til din forskning, er softwaren frit tilg\u00e6ngelig, og alle fra det videnskabelige samfund har lov til at bruge den og hj\u00e6lpe Garcia-Fossa og Gaal med at forbedre programmet.<\/p>\n\n\n\n

 ____<\/p>\n\n\n\n

Hvordan er din Mind the Graph-oplevelse indtil videre? Hj\u00e6lp os med at forbedre vores platform for dig og for en masse andre forskere ved at skrive en Mind the Graph-anmeldelse. Fort\u00e6l os om din oplevelse, bare klik her<\/a>. <\/p>","protected":false},"excerpt":{"rendered":"

PyScratch er en ny open source-software implementeret i Python til analyse af migrationsdata, med en brugervenlig gr\u00e6nseflade, der g\u00f8r det muligt for forskere med f\u00e5 eller ingen programmeringsf\u00e6rdigheder at bruge den. Softwaren blev designet i et partnerskab mellem tre brasilianske forskere i NanoCell Interactions-laboratoriet p\u00e5 University of Campinas i 2017. Det blev [...]<\/p>","protected":false},"author":4,"featured_media":12133,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[959,28],"tags":[817,554,964],"yoast_head":"\nA new tool for processing spatial and temporal information<\/title>\n<meta name=\"description\" content=\"Read this blog to know what PyScratch is and how that new tool processes spatial and temporal information from scratch assays.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/mindthegraph.com\/blog\/da\/saggi-pyscratch-spatial-and-temporal-information-from-scratch\/\" \/>\n<meta property=\"og:locale\" content=\"da_DK\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A new tool for processing spatial and temporal information\" \/>\n<meta property=\"og:description\" content=\"Read this 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