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diff --git a/notes/lec01_intro b/notes/lec01_intro
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+
+top down approach:
+    start with data, do stats, make predictions
+    see also Ma'ayan coursera course, "Network Analysis in Systems Bio"
+
+bottom up approach:
+    start with a model, run simulations to make predictions
+    scope: ODE, dynamics
+    beyond: parameter estimations, PDE, stochastics
+
+7 weeks, 25 lectures, 20 minutes each, 3-4 a week
+questions at the end of lectures, "just for self"
+5x homework assignments, required
+
+will discuss neuron firing a bit
+
+impression: will be very motivated
diff --git a/notes/lec02_matlab1 b/notes/lec02_matlab1
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+
+'format compact' => less syntax
+
+self assess:
+    C) 13x4
+    E) vertcat; different columns
+
+### julia notes:
+
+built-in types seem to default to just an array instead of, eg, 3x1 or 1x3.
+
+can transform with "'"; A'' != A?
+
+to vert/horiz cat, need to explicitly 
+
+julia> size([1,2,3])
+(3,)
+
+julia> size([1,2,3]')
+(1,3)
+
+julia> size([1,2,3]'')
+(3,1)
+
diff --git a/notes/lec03_matlab2 b/notes/lec03_matlab2
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+
+### julia notes
+
+for plotting, 'winston' is simple and matlab-like
+              'gadfly' is nice/correct, using design paradigms
+              'pyplot' is matplotlib
+
+for this class, at least to start, i'm going to try winston.
+
+Pkg.add("Winston")
+using Winston
+plot( cumsum(randn(1000)) )
+
+in winston, fplot() is nice for plotting functions over ranges