I am heating up different protein solutions and measuring their absorbance as it changes in time. I am running the same experiment multiple times for each condition. I would like to eventually get a single time-series of absorbance values for each condition - the average behavior, you might say.
The problem is, that the machine which measures the absorbance does not have a constant sampling frequency across runs, but each run it may be different (it depends on the number of conditions I run in parallel). The sample rate is constant within a single run.
A peak of the dataset for a single condition (time is in seconds):
Run 1:
time;lys
14;0,295
30;0,294
46;0,295
62;0,295
78;0,296
94;0,296
110;0,296
126;0,297
142;0,297
158;0,297
174;0,298
190;0,299
206;0,299
222;0,3
238;0,301
254;0,303
270;0,304
286;0,307
302;0,309
318;0,313
334;0,316
350;0,319
366;0,322
382;0,327
398;0,331
414;0,335
430;0,34
....
Run 2:
time;lys
14;0,263
31;0,264
48;0,265
65;0,265
82;0,266
99;0,266
116;0,267
133;0,268
150;0,268
167;0,268
184;0,269
201;0,27
218;0,27
235;0,271
252;0,273
269;0,275
286;0,277
303;0,279
320;0,282
337;0,286
354;0,29
371;0,294
388;0,298
405;0,302
...
Unfortunately, I cannot rerun the experiment with a constant frequency across runs. Can I still construct an averaged-out time-series from these runs?