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Mass-spectrometry-based proteomics enables the high-throughput identification and quantification of proteins, including sequence variants and post-translational modifications (PTMs) in biological samples. However, most workflows require that such variations be included in the search space used to analyze the data, and doing so remains challenging with most analysis tools. In order to facilitate the search for known sequence variants and PTMs, the Proteomics Standards Initiative (PSI) has designed and implemented the PSI extended FASTA format (PEFF). PEFF is based on the very popular FASTA format but adds a uniform mechanism for encoding substantially more metadata about the sequence collection as well as individual entries, including support for encoding known sequence variants, PTMs, and proteoforms. The format is very nearly backward compatible, and as such, existing FASTA parsers will require little or no changes to be able to read PEFF files as FASTA files, although without supporting any of the extra capabilities of PEFF. PEFF is defined by a full specification document, controlled vocabulary terms, a set of example files, software libraries, and a file validator. Popular software and resources are starting to support PEFF, including the sequence search engine Comet and the knowledge bases neXtProt and UniProtKB. Widespread implementation of PEFF is expected to further enable proteogenomics and top-down proteomics applications by providing a standardized mechanism for encoding protein sequences and their known variations. All the related documentation, including the detailed file format specification and example files, are available at http://www.psidev.info/peff .

Motivation Biological network analysis for high-throughput biomedical data interpretation relies heavily on topological characteristics. Networks are commonly composed of nodes representing genes or proteins that are connected by edges when interacting. In this study, we use the rich information available in the Reactome pathway database to build biological networks accounting for small molecules and proteoforms modeled using protein isoforms and post-translational modifications to study the topological changes induced by this refinement of the network representation. Results We find that improving the interactome modeling increases the number of nodes and interactions, but that isoform and post-translational modification annotation is still limited compared to what can be expected biologically. We also note that small molecule information can distort the topology of the network due to the high connectedness of these molecules, which does not necessarily represent the reality of biology. However, by restricting the connections of small molecules to the context of biochemical reactions, we find that these improve the overall connectedness of the network and reduce the prevalence of isolated components and nodes. Overall, changing the representation of the network alters the prevalence of articulation points and bridges globally but also within and across pathways. Hence, some molecules can gain or lose in biological importance depending on the level of detail of the representation of the biological system, which might in turn impact network-based studies of diseases or druggability. Availability and implementation Networks are constructed based on data publicly available in the Reactome Pathway knowledgebase: reactome.org. [ABSTRACT FROM AUTHOR]

The photoelectrochemical (PEC) properties of sputtered aluminum doped hydrogenated amorphous silicon carbide thin films grown on p-type crystalline silicon substrates were investigated in 1 M solution under chopped light illumination. Optical and structural properties of the top absorber layer were systematically assessed after post-deposition isochronical annealing treatments. Samples exhibited a noticeable improvement of the opto-electronic properties after thermal treatments. In addition, an abrupt enhancement of the photocurrent was observed reaching a saturation value of 17 mA cm−2 at −1.75 V vs. Ag/AgCl (3.5 M KCl). In this research we propose that this enhancement effect is associated to a charge transfer kinetic mechanism influenced by surface states and the p-type substrate. The latter most likely due to the space charge region extending beyond the absorber layer reaching the substrate. Current density-potential and electrochemical impedance spectroscopy measurements in dark revealed a reduction of the native layer at cathodic potentials higher than −1 V vs. Ag/AgCl (3.5 M KCl), which contributes to the high charge transfer kinetic of the system. We believe that these results will contribute to understand the substrate influence in the PEC performance of top absorber layers in multilayer structures for solar water splitting. [ABSTRACT FROM AUTHOR]

Ph y s. 54 (2021) 26960 1 (3pp) ht tps://doi.or g/1 0.1 088/1 361-6463/abef ee Er r at um: Anal y sis of the ph y sical and phot oelectr oc hemical pr oper ties of c-Si(p)/a-SiC:H(p) phot ocathodes f or solar w at er split ting (2021 J. Ph y s. D: Appl. J our nal of Ph y sics D: Applied Ph y sics J. Ph y s. D: Appl. Erratum: Analysis of the physical and photoelectrochemical properties of c-Si(p)/a-SiC:H(p) photocathodes for solar water splitting (2021 J. Phys. [Extracted from the article]

In biological and medical sciences, high throughput analytical methods are now commonly used to investigate samples of different conditions, e.g., patients versus controls. Systemic functional analyses emerged as a reference method to go beyond a list of regulated compounds, and identify activated or inactivated biological functions. This approach holds the promise for a better understanding of biological systems, of the mechanisms involved in disease progression, and thus improved diagnosis, prognosis, and treatment. In this chapter, we present a simple workflow to conduct pathway analyses on biological data using the freely available Reactome platform (http://www.reactome.org).