Advances in high-throughput proteomics have led to a rapid increase in the number, size, and complexity of the associated data sets. Managing and extracting reliable information from such large series of data sets require the use of dedicated software organized in a consistent pipeline to reduce, validate, exploit, and ultimately export data. The compilation of multiple mass-spectrometry-based identification and quantification results obtained in the context of a large-scale project represents a real challenge for developers of bioinformatics solutions. In response to this challenge, we developed a dedicated software suite called hEIDI to manage and combine both identifications and semiquantitative data related to multiple LC-MS/MS analyses. This paper describes how, through a user-friendly interface, hEIDI can be used to compile analyses and retrieve lists of nonredundant protein groups. Moreover, hEIDI allows direct comparison of series of analyses, on the basis of protein groups, while ensuring consistent protein inference and also computing spectral counts. hEIDI ensures that validated results are compliant with MIAPE guidelines as all information related to samples and results is stored in appropriate databases. Thanks to the database structure, validated results generated within hEIDI can be easily exported in the PRIDE XML format for subsequent publication. hEIDI can be downloaded from http://biodev.extra.cea.fr/docs/heidi .
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http://dx.doi.org/10.1021/acs.jproteome.5b00853 | DOI Listing |
Curr Med Chem
January 2025
Department of Electronics & Communication Engineering, Jaypee University of Information Technology, Solan, H.P., India.
A planktonic population of bacteria can form a biofilm by adhesion and colonization. Proteins known as "adhesins" can bind to certain environmental structures, such as sugars, which will cause the bacteria to attach to the substrate. Quorum sensing is used to establish the population is dense enough to form a biofilm.
View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
School of Materials and Energy, Lanzhou University (LZU), Lanzhou 730000, China.
Complementary neural network circuits combining multifunctional high-performance p-type with n-type organic artificial synapses satisfy sophisticated applications such as image cognition and prosthesis control. However, implementing the dual-modal memory features that are both volatile and nonvolatile in a synaptic transistor is challenging. Herein, for the first time, we propose a single vertical n-type organic synaptic transistor (VNOST) with a novel polymeric organic mixed ionic-electronic conductor as the core channel material to achieve dual-modal synaptic learning/memory behaviors at different operating current densities via the formation of an electric double layer and the reversible ion doping.
View Article and Find Full Text PDFNature
January 2025
National Disease Research Interchange, Philadelphia, PA, USA.
Many human diseases are the result of early developmental defects. As most paediatric diseases and disorders are rare, children are critically underrepresented in research. Functional genomics studies primarily rely on adult tissues and lack critical cell states in specific developmental windows.
View Article and Find Full Text PDFSci Data
January 2025
Department of Molecular Science and Technology, Ajou University, Suwon, 16499, Republic of Korea.
Chinese hamster ovary (CHO) cells play a pivotal role in the production of recombinant therapeutics. In the present study, we conducted a genome-scale pooled CRISPR knockout (KO) screening using a virus-free, recombinase-mediated cassette exchange-based platform in CHO-K1 host and CHO-K1 derived recombinant cells. Genome-wide guide RNA (gRNA) amplicon sequencing data were generated from cell libraries, as well as short- and long-term KO libraries, and validated through phenotypic assessment and gRNA read count distribution.
View Article and Find Full Text PDFSci Data
January 2025
Julius Kühn Institute (JKI), Federal Research Centre for Cultivated Plants, Institute for Breeding Research on Fruit Crops, Pillnitzer Platz 3a, 01326, Dresden-Pillnitz, Germany.
The German Fruit Genebank is a decentralized network focused on coordinating various germplasm collections across Germany to conserve and utilize the genetic resources of native fruit species. This aim emphasizes the necessity of trueness-to-type validation of genetic resources based on pomological and molecular characteristics. Between 2009 and 2021, multiple projects were undertaken to create an inventory of the apple (Malus ssp.
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