Sentence examples for steps we extracted from inspiring English sources

After applying all these preprocessing steps, we extracted a subset (ACD2) of 123,927 molecules from ACD1 and a subset (TCMCD2) of 33,961 molecules from TCMCD1, and both subsets have similar molecular weight (MW < 600) distributions to that of the MDDR subset (MDDR1).

To do so, we first constructed a p21 regulatory network using the following steps: We extracted miRNA-target interactions from the publication of Wu et al. [ 23 ] where a list of predicted p21-regulating miRNAs was subjected to experimental validation.

In the first step, we extracted temporal variations of the minimum slant range, corresponding elevation angle, and effective reflection height (Eq. (4)) of one-hop GB echoes.

For the first step, we extracted TLE data using the SGP4 code to obtain the position and velocity vectors of each satellite.

Based on the gene forest established in the previous step, we extracted all gene pairs in the same gene subsets.

In a posterior step, we extracted a sub-network considering only the regulatory interactions of all known B. subtilis TFs and σ factors.

In a posterior step, we extracted a sub-network consisting of only the regulatory interactions of all known B. subtilis TFs and σ factors (54 and 16, respectively).

In short, in the first step, we extracted existing knowledge from a disease chemical biology database to generate compound-specific human protein networks.

In a first step, we extracted all index symptoms (for example "Signs of shock", "Pain on the low right side") listed in the paediatric telephone protocol for abdominal pain (Please see left column of Table  1 for details).

To address this point in a first step, we extracted oriented contours from 128 different natural images (see Materials and Methods) by filtering them along the orientation dimension in Fourier space.

As a first step, we extracted from the filtered model (best model, proteins chromosomes) data set of the P. tricornutum data base (http://genome.jgi-psf.org/Phatr2/Phatr2.download.ftp.html), those protein models exceeding a 50% cutoff in the hidden markov model SP prediction of the SignalP 3.0 server (http://www.cbs.dtu.dk/services/SignalP/).dtu.dk/services/SignalP/