Summary

The validation process proposed has two pipelines for filtering PPIs predicted by some IN SILICO detection method, both pipelines can be executed separately. The first pipeline (i) filter according to association rules of cellular locations extracted from HINT database. The second pipeline (ii) filter according to scientific papers where both proteins in the PPIs appear in interaction context in the sentences.

The pipeline (i) starts extracting cellular component annotations from ...

Summary

PredPrIn is a scientific workflow to predict Protein-Protein Interactions (PPIs) using machine learning to combine multiple PPI detection methods of proteins according to three categories: structural, based on primary aminoacid sequence and functional annotations.

PredPrIn contains three main steps: (i) acquirement and treatment of protein information, (ii) feature generation, and (iii) classification and analysis.

(i) The first step builds a knowledge base with the available annotations ...

Summary

HPPIDiscovery is a scientific workflow to augment, predict and perform an insilico curation of host-pathogen Protein-Protein Interactions (PPIs) using graph theory to build new candidate ppis and machine learning to predict and evaluate them by combining multiple PPI detection methods of proteins according to three categories: structural, based on primary aminoacid sequence and functional annotations.

HPPIDiscovery contains three main steps: (i) acquirement of pathogen and host proteins ...

The ultimate-level complexity workflow is one among a collection of workflows designed to address tasks up to CTF estimation. In addition to the functionalities provided by layer 0 and 1 workflows, this workflow aims to enhance the quality of both acquisition images and processing.

Quality control protocols

…

Combination of methods

• CTF consensus
• New methods to compare ctf estimations
• CTF xmipp criteria (richer parameters i.e. ice detection)

Advantages: 

• Control of ...

This repository contains the python code to reproduce the experiments in Dłotko, Gurnari "Euler Characteristic Curves and Profiles: a stable shape invariant for big data problems"

This workflow represents the Default ML Pipeline for AutoML feature from MLme. Machine Learning Made Easy (MLme) is a novel tool that simplifies machine learning (ML) for researchers. By integrating four essential functionalities, namely data exploration, AutoML, CustomML, and visualization, MLme fulfills the diverse requirements of researchers while eliminating the need for extensive coding efforts. MLme serves as a valuable resource that empowers researchers of all technical levels to leverage ...

We present an R script that describes the workflow for analysing honey bee (Apis mellifera) wing shape. It is based on a dataset of wing images and landmark coordinates available at Zenodo: https://doi.org/10.5281/zenodo.8128010. The dataset can be used as a reference for the identification of local bees from southern Kazakhstan, which most probably belong to the subspecies Apis mellifera pomonella. It was compared with data from Nawrocka et al. (2018), available at Zenodo: ...

This workflow is designed to analyze to a multi-omics data set that comprises genome-wide DNA methylation profiles, targeted metabolomics, and behavioral data of two cohorts that participated in the ACTION Biomarker Study (ACTION, Aggression in Children: Unraveling gene-environment interplay to inform Treatment and InterventiON strategies. (Boomsma 2015, Bartels 2018, Hagenbeek 2020, van Dongen 2021, Hagenbeek 2022). The ACTION-NTR cohort consists of twins that are either longitudinally concordant ...

GERONIMO

Introduction

GERONIMO is a bioinformatics pipeline designed to conduct high-throughput homology searches of structural genes using covariance models. These models are based on the alignment of sequences and the consensus of secondary structures. The pipeline is built using Snakemake, a workflow management tool that allows for the reproducible execution of analyses on various computational platforms.

The idea for developing GERONIMO emerged from a comprehensive search for [telomerase ...

About SnakeMAGs

SnakeMAGs is a workflow to reconstruct prokaryotic genomes from metagenomes. The main purpose of SnakeMAGs is to process Illumina data from raw reads to metagenome-assembled genomes (MAGs). SnakeMAGs is efficient, easy to handle and flexible to different projects. The workflow is CeCILL licensed, implemented in Snakemake (run on multiple cores) and available ...