Not Available

Not AvailableNot AvailableAlignment and comparison of protein 3D structures is an important and fundamental task in structural biology to study evolutionary, functional and structural relatedness among proteins. Since two decades, the research on protein structure alignment has been taken up on priority and numbers of research articles are being published. There are incremental advances over previous efforts, and still these methods continue to improve over the time and still this is an open problem in structural biology. A novel methodology has been developed for comparing protein 3D structure by employing conversion of pair of protein 3D structures into 2D graphs (undirected weighted graph), partitioning of 2D graphs into sub-graphs, matching sub-graphs with main graphs and finally these sub-graphs matches calculates similarity between the pair of proteins. The proposed method has been implemented in MATLAB and R Package. The performance of the developed methodology is tested with four existing best methods such as CE, jFATCAT, TM_Align and Dali on 100 proteins benchmark dataset with SCOP database. The proposed method is efficient in terms of time complexity, accuracy, grouping of proteins in relevant structural groups and provides additional information towards non-bonded interactions and sub-graphs indicates the dominance of secondary structure.Not Availabl

Not Available

Not AvailableToday, large volume of sequence and structural data is publically available in the form of biological databases based on integrated effort of molecular biology laboratories throughout the world and advances in information technology. A global challenge in bioinformatics is the rationalization of the huge amount of sequences and structural data with a view not only to derive efficient and useful meaning from this data, but also for designing sharper analytical tools. The analytical tools are required for conversion of sequence data/information into biochemical and biophysical properties and to decipher the structural, functional and evolutionary clues encoded in the data. Pattern matching is one of main important aspects in the analysis of biological sequence and structure data. The alignment and comparison of protein 3D structures are very important and fundamental task in structural biology to study evolutionary and structural relatedness with other proteins and helps biologists to understand various functions and evolution from these structures to identify its structural neighbors. In addition to this, databases of three-dimensional protein structures became so large that fast search tools and comparison methods are required. The 3D structure comparison play a key role in understanding the diversity of structure space by analyzing and deriving interesting scientific insights in the existing vast structural databases. It is important to note that an increase in deposited structures does not just contain quantity, but also variety, complexity, vulnerability, and singularity. Hence, comparison tools are essentially required not only to improve accuracy and coverage but also reduce time complexity. Protein sequence uniquely determines a structure in its native environment. This structural information is vital in understanding the function of a protein. In last one and an half decade, the research on protein structure comparison has been taken up on priority basis and numbers of research articles were exists in literature. There are incremental advances over previous efforts, and still methods are being development for further improvement. The graph theory approaches can be used for protein 3D structure comparison. Graph models can be created using various graph parameters. Generally, graph theory is used to represent/decipher complex spatial structures which are mutually connected and dependent. The 3D structure of protein is a complex structure. The atom level analysis may yield better result in 3D structure analysis than any other method. Considering these important points, the project has been formulated to develop a tool for comparison of protein 3D structure using graph theoretic approach. We have developed two novel methods for comparison of 3D structure based on (1) graph partition and (2) graph properties. Both methods have been implemented in MATLAB by writing codes for various functions. The performance of the developed methodologies is tested with two existing best methods such as CE and jFATCAT on 100 proteins benchmark dataset with SCOP (Structural Classification Of Proteins) database. The proposed methods performed better in terms of classification accuracy and time complexity.Not Availabl

Not Available

Not AvailableDNA marker plays important role as valuable tools to increase crop productivity by finding plausible answers to genetic variations and linking the Quantitative Trait Loci (QTL) of beneficial trait. Prior approaches in development of Short Tandem Repeats (STR) markers were time consuming and inefficient. Recent methods invoking the development of STR markers using whole genomic or transcriptomics data has gained wide importance with immense potential in developing breeding and cultivator improvement approaches. Availability of whole genome sequences and in silico approaches has revolutionized bulk marker discovery. We report world’s first sugarbeet whole genome marker discovery having 145 K markers along with 5 K functional domain markers unified in common platform using MySQL, Apache and PHP in SBMDb. Embedded markers and corresponding location information can be selected for desired chromosome, location/ interval and primers can be generated using Primer3 core, integrated at backend. Our analyses revealed abundance of ‘mono’ repeat (76.82%) over ‘di’ repeats (13.68%). Highest density (671.05 markers/Mb) was found in chromosome 1 and lowest density (341.27 markers/Mb) in chromosome 6. Current investigation of sugarbeet genome marker density has direct implications in increasing mapping marker density. This will enable present linkage map having marker distance of 2 cM, i.e. from 200 to 2.6 Kb, thus facilitating QTL/gene mapping. We also report e-PCR-based detection of 2027 polymorphic markers in panel of five genotypes. These markers can be used for DUS test of variety identification and MAS/GAS in variety improvement program. The present database presents wide source of potential markers for developing and implementing new approaches for molecular breeding required to accelerate industrious use of this crop, especially for sugar, health care products, medicines and color dye. Identified markers will also help in improvement of bioenergy trait of bioethanol and biogas production along with reaping advantage of crop efficiency in terms of low water and carbon footprint especially in era of climate change.Not Availabl

Not Available

Not AvailableCoconut (Cocos nuciferaL.) has global significance in agriculture and industries due to its nutritional andmedicinal properties. Coconut Root Wilt Disease (RWD) causes huge economic loss, thus molecularapproach for improved varieties is needed. Since whole genome sequence is unavailable, transcriptomicapproach is imperative for deciphering pathways as well as genic region marker discovery from con-trasting genotypes. This is thefirst report of RWD transcriptome database having candidate genes andpathway discovery along with genic simple sequence repeats, SNPs, indels to be used as functionaldomain markers. A relational database, CnTDB (http://webtom.cabgrid.res.in/cntdb/), based on three-tierarchitecture has been developed having 285235 transcripts with all blast information, annotations,pathways, 22021 DEGs, transcriptional factors, 10126 and 97117 SSR markers mined from DEGs anddenovotranscriptome assembly, respectively. Putative markers with primers can be valuable genomicresource in endeavor of RWD resistant variety development for higher coconut productivity.Not Availabl

Not Available

Not AvailableNot AvailableNot Availabl

Not Available

Not AvailableOnion (Allium cepa L.), often regarded as a crop having an antediluvian coexistence with humans, is by far one of the most challenging plant species to be worked on, especially with respect to delineating its genomic information. It is considered as a plant of immense culinary and medicinal importance. However, there are very limited genomic ventures that have so far been established that could shed light on some of the most captivating aspects of the onion genome. Onion Genomic Resource (OGR), with three-tier architecture, is the first of its kind, comprehensive web-resource/database, built in MySQL database and PHP that catalogues the genomic developments specific to onion. It houses information of assembly of 20,204 publicly available onion expressed sequence tags (ESTs), available 20,755 assembled transcripts and 249,987 unigenes from Allium cepa transcriptome shotgun assembly (TSA) along with their annotations and functional significance. A total of 1915 SSRs from Onion ESTs and123,282 SSRs from Onion TSA data have been catalogued in OGR. Also, 135,424 SNPs and 11,891 Indels identified from Onion TSA data as well as 15 and 13 SNPs and Indels identified, respectively from Onion ESTs have been put in database. The resource also contains information of gene annotations, linked with KEGG pathways and 7 previously reported and 1 predicted onion miRNAs with their associated targets, which range from cytoplasmic globular proteins to membrane ion channels. Additionally, gene prediction was carried out for the unannotated sequences, of which few were observed to harbor coding regions for novel protein coding genes and transcripts that so far have not yet been identified. Over 200 different ready-to-use experimentally validated molecular markers were also mined from the existing literature to further enrich the lab-based studies targeting variety improvement. The OGR can be useful for onion molecular breeders as well as a valuable tool for confirmation of predicted ORF once the whole genome of onion is sequenced. The OGR is an open resource freely accessible at http://webtom.cabgrid.res.in/ogr/Not Availabl

Not Available

Not AvailableSmall cardamom (Elettaria cardamomum), grown in limited coastal tropical countries is one of the costliest and widely exported agri-produce having global turnover of >10 billion USD. Mosaic/marble disease is one of the major impediments that requires understanding of disease at molecular level. Neither whole genome sequence nor any genomic resources are available, thus RNA seq approach can be a rapid and economical alternative. De novo transcriptome assembly was done with Illumina Hiseq data. A total of 5317 DEGs, 2267 TFs, 114 pathways and 175,952 genic region putative markers were obtained. Gene regulatory network analysis deciphered molecular events involved in marble disease. This is the first transcriptomic report revealing disease mechanism mediated by perturbation in auxin homeostasis and ethylene signalling leading to senescence. The web-genomic resource (SCMVTDb) catalogues putative molecular markers, candidate genes and transcript information. SCMVTDb can be used in germplasm improvement against mosaic disease in endeavour of small cardamom productivity.Not Availabl