app for non-IT biologists, by which they can easily execute massive and complex analysis. is a protocol for bioinformaticians, by which they can easily publish workflows: and cli tools for that.
app for non-IT biologists, by which they can easily execute massive and complex analysis. is a protocol for bioinformaticians, by which they can easily publish workflows: and cli tools for that. なにつくってんの
app for non-IT biologists, by which they can easily execute massive and complex analysis. is a protocol for bioinformaticians, by which they can easily publish workflows: and cli tools for that. なにつくってんの Bio- informatics meets Go
Need to parse huge sized files ◦ DNA, RNA, Proteins… ~10TB • by using massive “Super Computer” ◦ CPU cores: 1200 ◦ Memory max: 2TB ◦ Disk: 12PiB • Good match to write goroutines ◦ all I can use!!
just with locating go/src and setting PATH • To deliver CLI tools to customers ◦ Amazing Cross Compiling ◦ you can shut them up who always say “it doesn’t work in my Python version”
.fna .ffn .faa .fra ◦ are ALL THE SAME THING • One of global standard data structure of Bio ◦ has a field which is dictionaries sometimes, lists sometimes, array of list sometimes, or simple strings sometimes ▪ so hard to decode to Go struct ;(
Advantage 2. Good match with strict protocoled industry/market 3. Excellently Easy to deliver CLI a. Even for server application, GAE/Go is very good for private web-app, cz it’s so economic
3. Excellently Easy to deliver CLI a. Even for server application, GAE/Go is very good for private web-app, cz it’s so economic 4. Except for low salary Wrapping up feelings Go in Bio-info Non-Web Context
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