5.3.2 Foldit

Foldit ne mai kyau bude kira domin sa ba masana su shiga a hanyar da fun.

The Netflix Prize, yayin evocative kuma bayyana, ba nuna cikakken kewayon bude kira ayyukan. Alal misali, a cikin Netflix Prize mafi yawan m mahalarta da shekaru horo a statistics da na'ura koyo. Amma, bude kira ayyukan iya unsa mahalarta da basu da m horo, kamar yadda aka kwatanta da Foldit, mai gina jiki nadawa game.

Protein nadawa ne tsari ta hanyar da sarkar amino acid daukan kan da siffar. Tare da mafi alhẽri fahimtar wannan tsari, ilmin halitta zai iya tsara sunadarai tare da takamaiman siffofi da cewa za a iya amfani da magani. Simplifying quite a bit, sunadarai ayan motsa zuwa ga mafi ƙasƙanci makamashi sanyi, wani sanyi cewa ma'aunan da daban-daban Firaministan kuma jan a cikin furotin (Figure 5.7). To, idan wani mai bincike yana so ya hango ko hasashen abin da siffar a cikin abin da mai gina jiki zai ninka, da mafita sauti mai sauki: kawai kokarin duk yiwu jeri, lissafi da kuzari, da kuma hango ko hasashen cewa furotin zai ninka a cikin mafi ƙasƙanci makamashi sanyi. Abin takaici, wannan zaluncin da karfi m cewa ya shafi kokarin duk yiwu jeri ne computationally yiwuwa domin akwai biliyoyin m jeri. Ko da tare da mafi m kwakwalwa samuwa a yau-da a foreseeable nan gaba-zaluncin da karfi ne kawai ba za su yi aiki. Saboda haka, ilmin halitta sun ɓullo da yawa wayo Algorithms to nagarta sosai bincika mafi ƙasƙanci makamashi sanyi. Amma, duk da m yawa na kimiyya da mai aiki da na'urar kwamfuta kokarin, wadannan Algorithms har yanzu suna da nisa daga m.

Figure 5.7: Protein nadawa. Image aka halitta da kuma sanya a cikin jama'a yankin da DrKjaergaard. Source: Wikimedia Commons.

Figure 5.7: Protein nadawa. Image aka halitta da kuma sanya a cikin jama'a yankin by "DrKjaergaard". Source: Wikimedia Commons .

David Baker da bincike kungiyar a Jami'ar Washington kasance wani ɓangare na al'umma na masana kimiyya aiki wajen samar da mafi alhẽri mai aiki da na'urar kwamfuta hanyoyin gina jiki nadawa. Domin waƙa abin da ke faruwa, alhãli kuwa Algorithms aka cranking bãya, Baker da kungiyar za lokaci-lokaci duba a allon-Tanadin cewa visualized ci gaba da Algorithms. Duk da yake kallon wadannan visualizations, Baker fara mamaki ko zai zama yiwu ga mutane su taimaka a cikin tsari, kuma ta haka ne ya fara Foldit, mai m, kuma m bude kira (Hand 2010) .

Foldit jũya tsari na gina jiki nadawa a cikin wani wasan da za a iya buga by kowa. Daga hangen zaman gaba na player, Foldit bayyana su zama a wuyar warwarewa (Figure 5.8). Players aka gabatar da uku-girma tangle furotin tsarin da zai iya yi operations- "tweak", "lilo", "sake gina" wato canja da siffar. By yin wadannan ayyukan 'yan wasan canja siffar da gina jiki, wanda a nuna ƙaruwa ko rage-rage m ci. Kafofin yada, da ci da aka lasafta bisa ga makamashi-matakin na yanzu sanyi. m-makamashi jeri haifar da mafi girma scores. A wasu kalmomin, da ci taimaka shiryar da 'yan wasan da suka bincika low-makamashi jeri. Wannan game ne kawai zai yiwu saboda-kamar tsinkaya movie ratings a Netflix Prize-gina jiki nadawa ne kuma a halin da ake ciki inda shi ne sauki don duba mafita daga samar da su.

Figure 5.8: Game allon for Foldit.

Figure 5.8: Game allon for Foldit.

Foldit ta m zane sa 'yan wasan da kadan m sanin Biochemistry gasa tare da mafi kyau Algorithms tsara da masana. Duk da yake mafi yawan 'yan wasan su ne ba musamman mai kyau a cikin aiki, akwai' yan wasan da kuma kananan teams da 'yan wasan suka yi kwarai. A gaskiya, a cikin wani kai-da-kai gasar hango ko hasashen tsarin 10 takamaiman sunadarai, Foldit 'yan wasan sun iya doke jihar-of-da-art gina jiki nadawa Algorithms sau biyar (Cooper et al. 2010) .

Foldit da Netflix kyauta ne daban-daban a cikin hanyoyi da dama, amma sai suka duka unsa bude kira ga mafita cewa su ne sauki don duba fiye da samar. Yanzu, za mu ga wannan tsarin a duk da haka wani daban saitin: lamban kira doka. Wannan karshe misali da wani kira a bayyane matsalar nuna cewa su kuma za a iya amfani da a saituna cewa ba a fili amenable to quantification.