Normalization for CCLE

I think the normalisation for CCLE is wrong.

Original code:
```{python}
# transfroms [0, -100] to [1,0] for curvecurator processing
def transform_activity_range(raw_df):
raw_df["Activity Data (median)"] = raw_df["Activity Data (median)"] / 100 + 1
raw_df["Amax"] = raw_df["Amax"] / 100 + 1
```

There is no explicit control column in the raw data, but there is this Amax value, which seems to be unique per cell line/drug combination. In the original supplementary methods, the authors state that
> Amax is the maximal activity value reached within a model

In the raw data, Amax is kind of the maximum response; it is always close to the response value associated with the highest dose (8µM). So it seems to be a positive control rather than a negative control, like DMSO would be.

I think it should be
```{python}
raw_df["response"] = 1 - raw_df["Activity Data (median)"]/raw_df["Amax"]
```

Start by locating the CCLE preprocessing entry point and the transform_activity_range function, then inspect how "Activity Data (median)", "Amax", and response are used downstream. Done means the CCLE response normalization follows the stated positive-control interpretation of Amax and remains valid for the generated input files.

Scritto dal modello di indicizzazione a partire dal testo della issue.