signaturization.md

@@ -5,25 +5,24 @@ The main feature of the CC is the automatic conversion of virtually any compound
 The central type of data are the signatures (one numerical vector per molecule), which are of four types:
 
 * `sign0` [Signatures type 0](#signatures-type-0): A sufficiently-processed version of the raw data. They usually show explicit knowledge, which enables connectivity and interpretation.
-* `sign1` [Signatures type 1](#signatures-type-1): A PCA/LSI-projected version of the data, retaining 90% of the variance. They keep most of the complexity of the original data and they can be used for *almost-exact* similarity calculations.
-* `sign2` [Signatures type 2](#signatures-type-2): Network embedding of the similarity matrix derived from signatures type 1. They have fixed length, which is convenient for machine learning, and capture both explicit *and* implicit similarity relationships in the data.
-* `sign3` [Signatures type 3](#signatures-type-3): Network embedding of observed *and* inferred similarity networks. Their added value, compared to signatures type 2, is that they can be derived for virtually *any* molecule in *any* dataset. :warning: These signatures are not calculated yet, and won't be in the near future.  
+* `sign1` [Signatures type 1](#signatures-type-1): A (TF-IDF) PCA/LSI-projected version of the signatures type 0, retaining 90% of the variance. They keep most of the complexity of the original data and they can be used for *almost-exact* similarity calculations.
+* `sign2` [Signatures type 2](#signatures-type-2): Network embedding of the similarity matrix derived from signatures type 1. They have a fixed length (e.g. 128-d), which is convenient for machine learning, and capture both explicit *and* implicit similarity relationships in the data.
+* `sign3` [Signatures type 3](#signatures-type-3): Network embedding of observed *and* inferred similarity networks. Their added value, compared to signatures type 2, is that they can be derived for virtually *any* molecule in *any* dataset.  
 
-Besides, there are other (auxiliary) types of data that may be of interest. The asterisk `*` denotes correspondence with signatures type `0`-`3`. Typically, we have the `1` version of the following in the repository.
+Besides, there are other auxiliary types of data that may be of interest. The asterisk `*` denotes correspondence with signatures type `0`-`3`.
 
-* `sims*` [Similarity vectors](#similarity-vectors): Full similarities stored as light `int8` data. Each molecule receives one such similarity vector per dataset. They may be observed `*_obs` or predicted `*_prd` similarities. These signatures are [only applicable to exemplary datasets](production-phase).
-* `neig*` [Nearest neighbors](#nearest-neighbors): Nearest neighbors search result. Currently, we consider the 1000-nearest neighbors, which is more than sufficient in any realistic scenario. For now, we only keep `neig1`.
-* `nprd*` [Predicted nearest neighbors](#predicted-nearest-neighbors): Predicted nearest neighbors. :warning: These are not available and will not be in the near future.
+* `neig*` [Nearest neighbors](#nearest-neighbors): Nearest neighbors search result. Currently, we consider the 1000-nearest neighbors, which is more than sufficient in any realistic scenario.
 * `clus*` [Clusters](#clusters): Centroids and labels of a k-means clustering.
 * `proj*` [2D Projections](#2d-projections): t-SNE 2D projections of the data.
+* `sims*` [Similarity vectors](#similarity-vectors): Full similarities stored as light `int8` data. Each molecule receives one such similarity vector per dataset. They may be observed `*_obs` or predicted `*_prd` similarities. These signatures are [only applicable to exemplary datasets](production-phase), and are mainly used for the [CC web resource](http://chemicalchecker.org).
 
-I consider the numbering `0`-`3` to be conceptually closed. However, further auxiliary data types may be introduced in the future. Note that all names have a 4-character code followed by a digit. Future data should stick to this nomenclature.
+Note that all names have a 4-character code followed by a digit. Future data should stick to this nomenclature.
 
 ## Commonalities
 
 *The following applies to all data types except the [similarity vectors](#similarity-vectors)* `sims*`*, which are of a very different nature due to their organization in the [folder structure](production-phase).*
 
-Every CC data will have the following methods:
+Every CC signature instance has the following methods:
 
 * `fit()`: Takes an input and learns to produce an output.
 * `predict()`: Uses the fitted models to go from input to output.