Additional file 1: Table S1. of SkipCPP-Pred: an improved and promising sequence-based predictor for predicting cell-penetrating peptides

Feature ranking of the proposed adaptive k-skip-2-g features. IG(x,c)a denotes information gain score. Higher IG(x,c) for a feature means the feature is more discriminative. Table S2. Performance of the Random Forest classifier with different tree numbers on the benchmark dataset CPP924 with the jackknife validation test. Note that the tree number is changed from 10 to 500 with the incremental step of 10. (DOCX 61 kb

AMPpred-MFA: An Interpretable Antimicrobial Peptide Predictor with a Stacking Architecture, Multiple Features, and Multihead Attention

Antimicrobial peptides (AMPs) are small molecular polypeptides that can be widely used in the prevention and treatment of microbial infections. Although many computational models have been proposed to help identify AMPs, a high-performance and interpretable model is still lacking. In this study, new benchmark data sets are collected and processed, and a stacking deep architecture named AMPpred-MFA is carefully designed to discover and identify AMPs. Multiple features and a multihead attention mechanism are utilized on the basis of a bidirectional long short-term memory (LSTM) network and a convolutional neural network (CNN). The effectiveness of AMPpred-MFA is verified through five independent tests conducted in batches. Experimental results show that AMPpred-MFA achieves a state-of-the-art performance. The visualization interpretability analyses and ablation experiments offer a further understanding of the model behavior and performance, validating the importance of our feature representation and stacking architecture, especially the multihead attention mechanism. Therefore, AMPpred-MFA can be considered a reliable and efficient approach to understanding and predicting AMPs

A comprehensive overview and evaluation of circular RNA detection tools - Fig 3

<p>Coverage between circRNA detection methods on <b>(a)</b> HeLa and <b>(b)</b> Hs68 RNase R–treated data. For a pair of methods (i, j), the number of candidates detected by each method and the common candidates between them are calculated, then the proportion of common candidates for each method can be further computed and depicted. Cells within the same column reflect proportions of candidates detected by a specific method (column name) covered by other methods (row names) while cells within the same row show the proportions of candidates detected by other methods (column names) covered by a specific method (row name). CE, CIRCexplorer; CF, circRNA_finder; circRNA, circular RNA; FC, find_circ; MS, MapSplice; SG, Segemehl; NCLS, NCLScan; PF, PTESFinder; RNase R, exonuclease that digests linear RNAs but preserves circRNAs; UB, UROBORUS.</p

Comparison of performance on the synthetic positive and mixed datasets in terms of sensitivity and precision rate.

<p>After filtering for candidates with ≥2 supporting reads, the number of candidates and true positives detected by each method were computed, then precision and sensitivity rate for each method were depicted.</p

A Comprehensive Analysis of miRNA/isomiR Expression with Gender Difference

<div><p>Although microRNAs (miRNAs) have been widely studied as epigenetic regulation molecules, fewer studies focus on the gender difference at the miRNA and isomiR expression levels. In this study, we aim to understand the potential relationships between gender difference and miRNA/isomiR expression through a comprehensive analysis of small RNA-sequencing datasets based on different human diseases and tissues. Based on specific samples from males and females, we determined that some miRNAs may be diversely expressed between different tissues and genders. Thus, these miRNAs may exhibit inconsistent and even opposite expression between males and females. According to deregulated miRNA expression profiles, some dominantly expressed miRNA loci were selected to analyze isomiR expression patterns using rates of dominant isomiRs. In some miRNA loci, isomiRs showed statistical significance between tumor and normal samples and between males and females samples, suggesting that isomiR expression patterns are not always invariable but may vary between males and females, as well as among different tissues, tumors, and normal samples. The divergence implicates the fluctuation in the expression of miRNA and its detailed expression at the isomiR levels. The divergence also indicates that gender difference may be an important factor that affects the screening of disease-associated miRNAs and isomiRs. This study suggests that miRNA/isomiR expression and gender difference may be more complex than previously assumed and should be further studied according to specific samples from males or females.</p></div

Additional file 3: of 70ProPred: a predictor for discovering sigma70 promoters based on combining multiple features

Table S2. Comparison prediction results of different k neighbors. (DOC 47 kb

Overview of circRNA candidates detected on the background dataset.

<p>Overview of circRNA candidates detected on the background dataset.</p

The flowchart to analyze miRNA/isomiR in the study.

<p>The flowchart to analyze miRNA/isomiR in the study.</p

Summary of accuracy measures on the positive and mixed datasets.

<p>Summary of accuracy measures on the positive and mixed datasets.</p

Comparison of circRNA candidates detected with and without RNase R treatment.

<p>Comparison of circRNA candidates detected with and without RNase R treatment.</p