Additional file 3: Figure S2. of CoSpliceNet: a framework for co-splicing network inference from transcriptomics data

The k-means clusters. The set of 7960 differentially expressed transcripts was clustered into 50 clusters using k-means algorithm. (PDF 1583 kb

L'Avenir de Luchon : journal scientifique, littéraire, annonces et réclames : guide général des baigneurs et des touristes aux eaux thermales, bains de mer de la France et de l'étranger

08 avril 19001900/04/08 (N7)-1900/04/08.Appartient à l’ensemble documentaire : MidiPyren

Additional file 2: Figure S2. of Identification of regulatory modules in genome scale transcription regulatory networks

Evaluation of different module-finding methods using simulated networks with different parameters. From top row to bottom row: mSize = 5, mSize = 15, mSize = 20. From left most column to right most column: targetNum = 5, targetNum = 15, targetNum = 20. (PDF 73 kb

Additional file 12: Table S9. of CoSpliceNet: a framework for co-splicing network inference from transcriptomics data

Enriched motifs in R regions of targets of each RBP. The motifs are shown as regular expressions from the MEME analysis. (XLSX 50 kb

Additional file 1: Figure S1. of CoSpliceNet: a framework for co-splicing network inference from transcriptomics data

Protein diversity analysis of the set of differentially expressed transcripts expressed during Arabidopsis embryo development. Two thousand three hundred forty-five genes were alternatively spliced. Protein diversity analysis was performed on 3008 SV pairs of these genes. a Effect of coding potential on peptide length differences of protein isoforms. b Relationship between the domain composition and coding potential. c Relationship between the peptide length ratio and coding potential. (PDF 130 kb

Additional file 6: Table S3. of Identification of regulatory modules in genome scale transcription regulatory networks

Experiments used in co-expression analysis of DAP-seq network (XLSX 12 kb

Additional file 5: Figure S3. of CoSpliceNet: a framework for co-splicing network inference from transcriptomics data

Distribution of the 146 SRPs in the super-clusters (PDF 124 kb

Additional file 4: Table S1. of Identification of regulatory modules in genome scale transcription regulatory networks

Module identified by CoReg in yeast-1-hybrid network. 0 means no module assignment (XLSX 18 kb

Additional file 19: Figure S4. of CoSpliceNet: a framework for co-splicing network inference from transcriptomics data

Step-by-step bioinformatics pipeline for co-splicing network construction from expression data (PDF 102 kb

The total number of mature leaves (A, B, C) and the total plant length (D, E, F) for three different lines of tomato grown with daily watering (control) or daily watering until water was withheld between day 20 and day 28 (mild-drought treatment).

<p>602 = ‘BHN 602’; 602/Cheong  =  refers to line ‘BHN 602’ scion grafted onto ‘Cheong Gang’ rootstock; 602/Jjak refers to line ‘BHN 602’ scion grafted onto ‘Jjak Kkung’ rootstock. Error bars represent two standard errors on each side of the mean. *  =  significant difference between control and mild-drought treated plants within a plant type (Student's t-test; p<0.05). δ  =  significant difference between 602/Jjak control plants and 602 control plants (Student's t-test; p<0.05).</p