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In recent decades, new technologies have made remarkable progress in helping to understand biological systems. Rapid advances in genomic profiling techniques such as microarrays or high-performance sequencing have brought new opportunities and challenges in the fields of computational biology and bioinformatics. Such genetic sequencing techniques allow large amounts of data to be produced, whose analysis and cross-integration could provide a complete view of organisms. As a result, it is necessary to develop new techniques and algorithms that carry out an analysis of these data with reliability and efficiency. This Special Issue collected the latest advances in the field of computational methods for the analysis of gene expression data, and, in particular, the modeling of biological processes. Here we present eleven works selected to be published in this Special Issue due to their interest, quality, and originality.

Research & information: general --- Biology, life sciences --- HIGD2A --- cancer --- DNA methylation --- mRNA expression --- miRNA --- quercetin --- hypoxia --- eQTL --- CRISPR-Cas9 --- single-cell clone --- fine-mapping --- power --- RNA N6-methyladenosine site --- yeast genome --- methylation --- computational biology --- deep learning --- bioinformatics --- hepatocellular carcinoma --- transcriptomics --- proteomics --- bioinformatics analysis --- differentiation --- Gene Ontology --- Reactome Pathways --- gene-set enrichment --- meta-analysis --- transcription factor --- binding sites --- genomics --- chilling stress --- CBF --- DREB --- CAMTA1 --- pathway --- text mining --- infiltration tactics optimization algorithm --- classification --- clustering --- microarray --- ensembles --- machine learning --- infiltration --- computational intelligence --- gene co-expression network --- murine coronavirus --- viral infection --- immune response --- data mining --- systems biology --- obesity --- differential genes expression --- exercise --- high-fat diet --- pathways --- potential therapeutic targets --- DNA N6-methyladenine --- Chou's 5-steps rule --- Convolution Neural Network (CNN) --- Long Short-Term Memory (LSTM) --- machine-learning --- chromatin interactions --- prediction --- genome architecture --- HIGD2A --- cancer --- DNA methylation --- mRNA expression --- miRNA --- quercetin --- hypoxia --- eQTL --- CRISPR-Cas9 --- single-cell clone --- fine-mapping --- power --- RNA N6-methyladenosine site --- yeast genome --- methylation --- computational biology --- deep learning --- bioinformatics --- hepatocellular carcinoma --- transcriptomics --- proteomics --- bioinformatics analysis --- differentiation --- Gene Ontology --- Reactome Pathways --- gene-set enrichment --- meta-analysis --- transcription factor --- binding sites --- genomics --- chilling stress --- CBF --- DREB --- CAMTA1 --- pathway --- text mining --- infiltration tactics optimization algorithm --- classification --- clustering --- microarray --- ensembles --- machine learning --- infiltration --- computational intelligence --- gene co-expression network --- murine coronavirus --- viral infection --- immune response --- data mining --- systems biology --- obesity --- differential genes expression --- exercise --- high-fat diet --- pathways --- potential therapeutic targets --- DNA N6-methyladenine --- Chou's 5-steps rule --- Convolution Neural Network (CNN) --- Long Short-Term Memory (LSTM) --- machine-learning --- chromatin interactions --- prediction --- genome architecture

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Hydrogen sulfide (H2S), which was previously considered to be toxic, is now regarded as a burgeoning endogenous gaseous transmitter. H2S plays a vital role in the mechanism of response/adaptation to adverse environmental conditions as well as crosstalk with other signaling molecules, including ROS, by affecting the corresponding gene expression and subsequent enzyme activities. Both H2S and ROS are potent signaling molecules that can provoke reversible and irreversible oxidative post-translational modifications on cysteine residues of proteins such as sulfenylation or persulfidation, affecting the redox status and function of the target proteins. The dynamic interplay between persulfidation and sulfenylation occurring on cysteine residues is of great importance in response to environmental changes.The present Special Issue of IJMS has the aim of providing the most current findings on the function of signaling molecules, including H2S and ROS, in higher plants, and it is open to different types of manuscripts, including original research papers, perspectives, or reviews where either ROS, H2S, or related molecules could be involved at the biochemical or physiological levels.

Mathematics & science --- Biology, life sciences --- Molecular biology --- antioxidant defense systems --- Cd stress --- hydrogen sulfide --- melatonin --- oxidative stress --- transportation and sequestration --- nitric oxide --- abscisic acid --- Ca2+ --- hydrogen peroxide --- abiotic stresses --- signal transmitters --- stomatal movement --- persulfidation --- drought stress --- nitrate reductase --- l-cysteine desulfhydrase --- chilling stress --- indole-3-acetic acid --- signaling pathway --- calcium deficiency --- endogenous H2S --- reactive oxygen species --- ERF2-bHLH2-CML5 module --- postharvest storage quality --- tomato --- cysteine desulfhydrase --- leaf senescence --- ARF --- auxin --- cold stress --- cucumber --- DREB --- module --- resistance --- root growth --- heavy metal --- salt --- DES1 --- ABI4 --- protein stability --- Brassica rapa --- mercury --- selenium --- biotic stress --- abiotic stress --- salicylic acid --- jasmonic acid --- ethylene --- phytohormones --- Arabidopsis --- manganese stress --- L-cysteine desulfhydrase --- antioxidant enzyme --- Allium --- garlic --- gas detector --- ion-selective microelectrode --- isozymes --- RBOHs --- signaling networks --- n/a

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This volume presents recent research achievements concerning the molecular genetic basis of agronomic traits in rice. Rice (Oryza sativa L.) is the most important food crop in the world, being a staple food for more than half of the world’s population. Recent improvements in living standards have increased the worldwide demand for high-yielding and high-quality rice cultivars. To achieve improved agricultural performance in rice, while overcoming the challenges presented by climate change, it is essential to understand the molecular basis of agronomically important traits. Recently developed techniques in molecular biology, especially in genomics and other related omics fields, can reveal the complex molecular mechanisms involved in the control of agronomic traits. As rice was the first crop genome to be sequenced, in 2004, molecular research tools for rice are well-established, and further molecular studies will enable the development of novel rice cultivars with superior agronomic performance.

Research & information: general --- Biology, life sciences --- Technology, engineering, agriculture --- chloroplast RNA splicing and ribosome maturation (CRM) domain --- intron splicing --- chloroplast development --- rice --- rice (Oryza sativa L.), grain size and weight --- Insertion/Deletion (InDel) markers --- multi-gene allele contributions --- genetic variation --- rice germplasm --- disease resistance --- microbe-associated molecular pattern (MAMP) --- Pyricularia oryzae (formerly Magnaporthe oryzae) --- Oryza sativa (rice) --- receptor-like cytoplasmic kinase (RLCK) --- reactive oxygen species (ROS) --- salinity --- osmotic stress --- combined stress --- GABA --- phenolic metabolism --- CIPKs genes --- shoot apical meristem --- transcriptomic analysis --- co-expression network --- tiller --- nitrogen rate --- rice (Oryza sativa L.) --- quantitative trait locus --- grain protein content --- single nucleotide polymorphism --- residual heterozygote --- rice (Oryza sativa) --- specific length amplified fragment sequencing --- Kjeldahl nitrogen determination --- near infrared reflectance spectroscopy --- heterosis --- yield components --- high-throughput sequence --- FW2.2-like gene --- tiller number --- grain yield --- CRISPR/Cas9 --- genome editing --- off-target effect --- heat stress --- transcriptome --- anther --- anthesis --- pyramiding --- bacterial blight --- marker-assisted selection --- foreground selection --- background selection --- japonica rice --- cold stress --- germinability --- high-density linkage map --- QTLs --- seed dormancy --- ABA --- seed germination --- chromosome segment substitution lines --- linkage mapping --- Oryza sativa L. --- chilling stress --- chlorophyll biosynthesis --- chloroplast biogenesis --- epidermal characteristics --- AAA-ATPase --- salicylic acid --- fatty acid --- Magnaporthe oryzae --- leaf senescence --- quantitative trait loci --- transcriptome analysis --- genetic --- epigenetic --- global methylation --- transgenic --- phenotype --- OsNAR2.1 --- dwarfism --- OsCYP96B4 --- metabolomics --- NMR --- qRT-PCR --- bHLH transcription factor --- lamina joint --- leaf angle --- long grain --- brassinosteroid signaling --- blast disease --- partial resistance --- pi21 --- haplotype --- high night temperature --- wet season --- dry season --- n/a

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This volume presents recent research achievements concerning the molecular genetic basis of agronomic traits in rice. Rice (Oryza sativa L.) is the most important food crop in the world, being a staple food for more than half of the world’s population. Recent improvements in living standards have increased the worldwide demand for high-yielding and high-quality rice cultivars. To achieve improved agricultural performance in rice, while overcoming the challenges presented by climate change, it is essential to understand the molecular basis of agronomically important traits. Recently developed techniques in molecular biology, especially in genomics and other related omics fields, can reveal the complex molecular mechanisms involved in the control of agronomic traits. As rice was the first crop genome to be sequenced, in 2004, molecular research tools for rice are well-established, and further molecular studies will enable the development of novel rice cultivars with superior agronomic performance.

Research & information: general --- Biology, life sciences --- Technology, engineering, agriculture --- chloroplast RNA splicing and ribosome maturation (CRM) domain --- intron splicing --- chloroplast development --- rice --- rice (Oryza sativa L.), grain size and weight --- Insertion/Deletion (InDel) markers --- multi-gene allele contributions --- genetic variation --- rice germplasm --- disease resistance --- microbe-associated molecular pattern (MAMP) --- Pyricularia oryzae (formerly Magnaporthe oryzae) --- Oryza sativa (rice) --- receptor-like cytoplasmic kinase (RLCK) --- reactive oxygen species (ROS) --- salinity --- osmotic stress --- combined stress --- GABA --- phenolic metabolism --- CIPKs genes --- shoot apical meristem --- transcriptomic analysis --- co-expression network --- tiller --- nitrogen rate --- rice (Oryza sativa L.) --- quantitative trait locus --- grain protein content --- single nucleotide polymorphism --- residual heterozygote --- rice (Oryza sativa) --- specific length amplified fragment sequencing --- Kjeldahl nitrogen determination --- near infrared reflectance spectroscopy --- heterosis --- yield components --- high-throughput sequence --- FW2.2-like gene --- tiller number --- grain yield --- CRISPR/Cas9 --- genome editing --- off-target effect --- heat stress --- transcriptome --- anther --- anthesis --- pyramiding --- bacterial blight --- marker-assisted selection --- foreground selection --- background selection --- japonica rice --- cold stress --- germinability --- high-density linkage map --- QTLs --- seed dormancy --- ABA --- seed germination --- chromosome segment substitution lines --- linkage mapping --- Oryza sativa L. --- chilling stress --- chlorophyll biosynthesis --- chloroplast biogenesis --- epidermal characteristics --- AAA-ATPase --- salicylic acid --- fatty acid --- Magnaporthe oryzae --- leaf senescence --- quantitative trait loci --- transcriptome analysis --- genetic --- epigenetic --- global methylation --- transgenic --- phenotype --- OsNAR2.1 --- dwarfism --- OsCYP96B4 --- metabolomics --- NMR --- qRT-PCR --- bHLH transcription factor --- lamina joint --- leaf angle --- long grain --- brassinosteroid signaling --- blast disease --- partial resistance --- pi21 --- haplotype --- high night temperature --- wet season --- dry season --- chloroplast RNA splicing and ribosome maturation (CRM) domain --- intron splicing --- chloroplast development --- rice --- rice (Oryza sativa L.), grain size and weight --- Insertion/Deletion (InDel) markers --- multi-gene allele contributions --- genetic variation --- rice germplasm --- disease resistance --- microbe-associated molecular pattern (MAMP) --- Pyricularia oryzae (formerly Magnaporthe oryzae) --- Oryza sativa (rice) --- receptor-like cytoplasmic kinase (RLCK) --- reactive oxygen species (ROS) --- salinity --- osmotic stress --- combined stress --- GABA --- phenolic metabolism --- CIPKs genes --- shoot apical meristem --- transcriptomic analysis --- co-expression network --- tiller --- nitrogen rate --- rice (Oryza sativa L.) --- quantitative trait locus --- grain protein content --- single nucleotide polymorphism --- residual heterozygote --- rice (Oryza sativa) --- specific length amplified fragment sequencing --- Kjeldahl nitrogen determination --- near infrared reflectance spectroscopy --- heterosis --- yield components --- high-throughput sequence --- FW2.2-like gene --- tiller number --- grain yield --- CRISPR/Cas9 --- genome editing --- off-target effect --- heat stress --- transcriptome --- anther --- anthesis --- pyramiding --- bacterial blight --- marker-assisted selection --- foreground selection --- background selection --- japonica rice --- cold stress --- germinability --- high-density linkage map --- QTLs --- seed dormancy --- ABA --- seed germination --- chromosome segment substitution lines --- linkage mapping --- Oryza sativa L. --- chilling stress --- chlorophyll biosynthesis --- chloroplast biogenesis --- epidermal characteristics --- AAA-ATPase --- salicylic acid --- fatty acid --- Magnaporthe oryzae --- leaf senescence --- quantitative trait loci --- transcriptome analysis --- genetic --- epigenetic --- global methylation --- transgenic --- phenotype --- OsNAR2.1 --- dwarfism --- OsCYP96B4 --- metabolomics --- NMR --- qRT-PCR --- bHLH transcription factor --- lamina joint --- leaf angle --- long grain --- brassinosteroid signaling --- blast disease --- partial resistance --- pi21 --- haplotype --- high night temperature --- wet season --- dry season