https://youtube.com/@sysbio
https://fac.iitg.ac.in/biplabbose
@code_lowered 2 + 3
@code_lowered 2 + 3.0
@code_lowered 2.0 + 3.0
Code better. Code smarter.
#JuliaLang #computing #sysbio #systemsbiology #qbio
@code_lowered 2 + 3
@code_lowered 2 + 3.0
@code_lowered 2.0 + 3.0
Code better. Code smarter.
#JuliaLang #computing #sysbio #systemsbiology #qbio
Toy models with few parameters > the design principles behind the complexity of Life.
True Systems Biology: fewer spreadsheets, more ‘Aha!’ moments. #sysbio #mathbio #physicsoflife
Toy models with few parameters > the design principles behind the complexity of Life.
True Systems Biology: fewer spreadsheets, more ‘Aha!’ moments. #sysbio #mathbio #physicsoflife
A = rand(5,5)
W = @view A[2:4,2:4] # take a peek, no copying
@views W[1:2, 1:2] .= 0 # sneakily mutate
A # check the mutation
#julialang #computing
A = rand(5,5)
W = @view A[2:4,2:4] # take a peek, no copying
@views W[1:2, 1:2] .= 0 # sneakily mutate
A # check the mutation
#julialang #computing
#justforfun #teaching #physicsoflife #physicsoflivingmatter
#justforfun #teaching #physicsoflife #physicsoflivingmatter
using DifferentialEquations, MonteCarloMeasurements
k = 1.0 ± 0.1
u0 = 1.0 ± 0
prob = ODEProblem((u,p,t)->-k*u, u0, (0,5))
sol = solve(prob)
mean(sol[end])
#JuliaLang #computing
using DifferentialEquations, MonteCarloMeasurements
k = 1.0 ± 0.1
u0 = 1.0 ± 0
prob = ODEProblem((u,p,t)->-k*u, u0, (0,5))
sol = solve(prob)
mean(sol[end])
#JuliaLang #computing
arxiv.org/abs/2511.17247
Perfect for my Systems Biology course.
#sysbio #complexsystem #graph #network #compbio #mathbio
arxiv.org/abs/2511.17247
Perfect for my Systems Biology course.
#sysbio #complexsystem #graph #network #compbio #mathbio
using Unitful
D = 0.01u"mm^2/s" # 0.01 mm^2 s^-1
t = 100u"s" # 100 s
√(2D*t) # 1.4142 mm
#julialang #computing #sysbio #systemsbiology
using Unitful
D = 0.01u"mm^2/s" # 0.01 mm^2 s^-1
t = 100u"s" # 100 s
√(2D*t) # 1.4142 mm
#julialang #computing #sysbio #systemsbiology
If I slap someone, they feel pain and may hit back. That’s real.
So clearly, I’m missing something much deeper. #justsaying
If I slap someone, they feel pain and may hit back. That’s real.
So clearly, I’m missing something much deeper. #justsaying
#complexsystem #PhysicsOfLife #sysbio
#complexsystem #PhysicsOfLife #sysbio
using Zygote
f(x) = x^2 + 3x + sin(x)
f'(2.0) # returns 6.58385
#Julialang #mathbio #qBio #compbio #sysbio #systemsbiology
using Zygote
f(x) = x^2 + 3x + sin(x)
f'(2.0) # returns 6.58385
#Julialang #mathbio #qBio #compbio #sysbio #systemsbiology
link.springer.com/article/10.1... #activematter #physicsoflife #physicalbiology #complexity
link.springer.com/article/10.1... #activematter #physicsoflife #physicalbiology #complexity
Math-Bio isn't just HPC runs— derivations & proofs matter too. As always, Julia helps.
using Symbolics
@variables x y a b c d m n
f = [a/(1+y^n)-b*x, c/(1+x^m)-d*y]
J = Symbolics.jacobian(f,[x,y])
#Julialang #mathbio #computaionalbiology #sysbio
Math-Bio isn't just HPC runs— derivations & proofs matter too. As always, Julia helps.
using Symbolics
@variables x y a b c d m n
f = [a/(1+y^n)-b*x, c/(1+x^m)-d*y]
J = Symbolics.jacobian(f,[x,y])
#Julialang #mathbio #computaionalbiology #sysbio
You (examiner): That statistics & conclusion are wrong. Needs correction for repeated tests.
Candidate: 🤔 (flustered).
Supervisor: No issues! 😡 This work is already published.
How often do you face such a situation?
#worldofbiologists #bio
You (examiner): That statistics & conclusion are wrong. Needs correction for repeated tests.
Candidate: 🤔 (flustered).
Supervisor: No issues! 😡 This work is already published.
How often do you face such a situation?
#worldofbiologists #bio
#complexsystem #physicsoflife #physicsoflivingmatter #systemsbiology
#complexsystem #physicsoflife #physicsoflivingmatter #systemsbiology
B = [3, 4, 5]
x = 9
x ∈ A ∪ B # -> false
Writing code using symbols in Julia feels like scribbling in a math notebook — except this one actually runs. It takes some time to get habituated, but then you get hooked.
#julialang #computing
B = [3, 4, 5]
x = 9
x ∈ A ∪ B # -> false
Writing code using symbols in Julia feels like scribbling in a math notebook — except this one actually runs. It takes some time to get habituated, but then you get hooked.
#julialang #computing