Displaying publications 61 - 80 of 119 in total

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  1. Choong YS, Mancera R, Lee VS
    Mol Biotechnol, 2024 Apr;66(4):567.
    PMID: 38337130 DOI: 10.1007/s12033-024-01073-1
    Matched MeSH terms: Computational Biology/methods
  2. Ashkani S, Yusop MR, Shabanimofrad M, Azady A, Ghasemzadeh A, Azizi P, et al.
    Curr Issues Mol Biol, 2015;17:57-73.
    PMID: 25706446
    Allele mining is a promising way to dissect naturally occurring allelic variants of candidate genes with essential agronomic qualities. With the identification, isolation and characterisation of blast resistance genes in rice, it is now possible to dissect the actual allelic variants of these genes within an array of rice cultivars via allele mining. Multiple alleles from the complex locus serve as a reservoir of variation to generate functional genes. The routine sequence exchange is one of the main mechanisms of R gene evolution and development. Allele mining for resistance genes can be an important method to identify additional resistance alleles and new haplotypes along with the development of allele-specific markers for use in marker-assisted selection. Allele mining can be visualised as a vital link between effective utilisation of genetic and genomic resources in genomics-driven modern plant breeding. This review studies the actual concepts and potential of mining approaches for the discovery of alleles and their utilisation for blast resistance genes in rice. The details provided here will be important to provide the rice breeder with a worthwhile introduction to allele mining and its methodology for breakthrough discovery of fresh alleles hidden in hereditary diversity, which is vital for crop improvement.
    Matched MeSH terms: Computational Biology/methods
  3. Ong WD, Voo LY, Kumar VS
    PLoS One, 2012;7(10):e46937.
    PMID: 23091603 DOI: 10.1371/journal.pone.0046937
    BACKGROUND: Pineapple (Ananas comosus var. comosus), is an important tropical non-climacteric fruit with high commercial potential. Understanding the mechanism and processes underlying fruit ripening would enable scientists to enhance the improvement of quality traits such as, flavor, texture, appearance and fruit sweetness. Although, the pineapple is an important fruit, there is insufficient transcriptomic or genomic information that is available in public databases. Application of high throughput transcriptome sequencing to profile the pineapple fruit transcripts is therefore needed.

    METHODOLOGY/PRINCIPAL FINDINGS: To facilitate this, we have performed transcriptome sequencing of ripe yellow pineapple fruit flesh using Illumina technology. About 4.7 millions Illumina paired-end reads were generated and assembled using the Velvet de novo assembler. The assembly produced 28,728 unique transcripts with a mean length of approximately 200 bp. Sequence similarity search against non-redundant NCBI database identified a total of 16,932 unique transcripts (58.93%) with significant hits. Out of these, 15,507 unique transcripts were assigned to gene ontology terms. Functional annotation against Kyoto Encyclopedia of Genes and Genomes pathway database identified 13,598 unique transcripts (47.33%) which were mapped to 126 pathways. The assembly revealed many transcripts that were previously unknown.

    CONCLUSIONS: The unique transcripts derived from this work have rapidly increased of the number of the pineapple fruit mRNA transcripts as it is now available in public databases. This information can be further utilized in gene expression, genomics and other functional genomics studies in pineapple.

    Matched MeSH terms: Computational Biology/methods
  4. Yew CW, Kumar SV
    Mol Biol Rep, 2012 Feb;39(2):1783-90.
    PMID: 21625851 DOI: 10.1007/s11033-011-0919-7
    MicroRNAs (miRNAs) are small RNAs (sRNAs) with approximately 21-24 nucleotides in length. They regulate the expression of target genes through the mechanism of RNA silencing. Conventional isolation and cloning of miRNAs methods are usually technical demanding and inefficient. These limitations include the requirement for high amounts of starting total RNA, inefficient ligation of linkers, high amount of PCR artifacts and bias in the formation of short miRNA-concatamers. Here we describe in detail a method that uses 80 μg of total RNA as the starting material. Enhancement of the ligation of sRNAs and linkers with the use of polyethylene glycol (PEG8000) was described. PCR artifacts from the amplification of reverse-transcribed sRNAs were greatly decreased by using lower concentrations of primers and reducing the number of amplification cycles. Large concatamers with up to 1 kb in size with around 20 sRNAs/concatamer were obtained by using an optimized reaction condition. This protocol provide researchers with a rapid, efficient and cost-effective method for the construction of miRNA profiles from plant tissues containing low amounts of total RNA, such as fruit flesh and senescent leaves.
    Matched MeSH terms: Computational Biology/methods
  5. Kumar S
    BMC Res Notes, 2015;8:9.
    PMID: 25595103 DOI: 10.1186/s13104-015-0976-4
    Cytochrome P450s (CYPs) are important heme-containing proteins, well known for their monooxygenase reaction. The human cytochrome P450 4X1 (CYP4X1) is categorized as "orphan" CYP because of its unknown function. In recent studies it is found that this enzyme is expressed in neurovascular functions of the brain. Also, various studies have found the expression and activity of orphan human cytochrome P450 4X1 in cancer. It is found to be a potential drug target for cancer therapy. However, three-dimensional structure, the active site topology and substrate specificity of CYP4X1 remain unclear.
    Matched MeSH terms: Computational Biology/methods*
  6. Abd Algfoor Z, Shahrizal Sunar M, Abdullah A, Kolivand H
    Brief Funct Genomics, 2017 03 01;16(2):87-98.
    PMID: 26969656 DOI: 10.1093/bfgp/elw002
    Metabolic pathways have become increasingly available for various microorganisms. Such pathways have spurred the development of a wide array of computational tools, in particular, mathematical pathfinding approaches. This article can facilitate the understanding of computational analysis of metabolic pathways in genomics. Moreover, stoichiometric and pathfinding approaches in metabolic pathway analysis are discussed. Three major types of studies are elaborated: stoichiometric identification models, pathway-based graph analysis and pathfinding approaches in cellular metabolism. Furthermore, evaluation of the outcomes of the pathways with mathematical benchmarking metrics is provided. This review would lead to better comprehension of metabolism behaviors in living cells, in terms of computed pathfinding approaches.
    Matched MeSH terms: Computational Biology/methods*
  7. Wongrattanakamon P, Lee VS, Nimmanpipug P, Sirithunyalug B, Chansakaow S, Jiranusornkul S
    Toxicol. Mech. Methods, 2017 May;27(4):253-271.
    PMID: 27996361 DOI: 10.1080/15376516.2016.1273428
    In this work, molecular docking, pharmacophore modeling and molecular dynamics (MD) simulation were rendered for the mouse P-glycoprotein (P-gp) (code: 4Q9H) and bioflavonoids; amorphigenin, chrysin, epigallocatechin, formononetin and rotenone including a positive control; verapamil to identify protein-ligand interaction features including binding affinities, interaction characteristics, hot-spot amino acid residues and complex stabilities. These flavonoids occupied the same binding site with high binding affinities and shared the same key residues for their binding interactions and the binding region of the flavonoids was revealed that overlapped the ATP binding region with hydrophobic and hydrophilic interactions suggesting a competitive inhibition mechanism of the compounds. Root mean square deviations (RMSDs) analysis of MD trajectories of the protein-ligand complexes and NBD2 residues, and ligands pointed out these residues were stable throughout the duration of MD simulations. Thus, the applied preliminary structure-based molecular modeling approach of interactions between NBD2 and flavonoids may be gainful to realize the intimate inhibition mechanism of P-gp at NBD2 level and on the basis of the obtained data, it can be concluded that these bioflavonoids have the potential to cause herb-drug interactions or be used as lead molecules for the inhibition of P-gp (as anti-multidrug resistance agents) via the NBD2 blocking mechanism in future.
    Matched MeSH terms: Computational Biology/methods*
  8. Seah CS, Kasim S, Saedudin RR, Md Fudzee MF, Mohamad MS, Hassan R, et al.
    Pak J Pharm Sci, 2019 May;32(3 Special):1395-1408.
    PMID: 31551221
    Numerous cancer studies have combined different datasets for the prognosis of patients. This study incorporated four networks for significant directed random walk (sDRW) to predict cancerous genes and risk pathways. The study investigated the feasibility of cancer prediction via different networks. In this study, multiple micro array data were analysed and used in the experiment. Six gene expression datasets were applied in four networks to study the effectiveness of the networks in sDRW in terms of cancer prediction. The experimental results showed that one of the proposed networks is outstanding compared to other networks. The network is then proposed to be implemented in sDRW as a walker network. This study provides a foundation for further studies and research on other networks. We hope these finding will improve the prognostic methods of cancer patients.
    Matched MeSH terms: Computational Biology/methods*
  9. Seman A, Bakar ZA, Isa MN
    BMC Res Notes, 2012;5:557.
    PMID: 23039132 DOI: 10.1186/1756-0500-5-557
    Y-Short Tandem Repeats (Y-STR) data consist of many similar and almost similar objects. This characteristic of Y-STR data causes two problems with partitioning: non-unique centroids and local minima problems. As a result, the existing partitioning algorithms produce poor clustering results.
    Matched MeSH terms: Computational Biology/methods*
  10. Jasper M, Schmidt TL, Ahmad NW, Sinkins SP, Hoffmann AA
    Mol Ecol Resour, 2019 Sep;19(5):1254-1264.
    PMID: 31125998 DOI: 10.1111/1755-0998.13043
    Understanding past dispersal and breeding events can provide insight into ecology and evolution and can help inform strategies for conservation and the control of pest species. However, parent-offspring dispersal can be difficult to investigate in rare species and in small pest species such as mosquitoes. Here, we develop a methodology for estimating parent-offspring dispersal from the spatial distribution of close kin, using pairwise kinship estimates derived from genome-wide single nucleotide polymorphisms (SNPs). SNPs were scored in 162 Aedes aegypti (yellow fever mosquito) collected from eight close-set, high-rise apartment buildings in an area of Malaysia with high dengue incidence. We used the SNPs to reconstruct kinship groups across three orders of kinship. We transformed the geographical distances between all kin pairs within each kinship category into axial standard deviations of these distances, then decomposed these into components representing past dispersal events. From these components, we isolated the axial standard deviation of parent-offspring dispersal and estimated neighbourhood area (129 m), median parent-offspring dispersal distance (75 m) and oviposition dispersal radius within a gonotrophic cycle (36 m). We also analysed genetic structure using distance-based redundancy analysis and linear regression, finding isolation by distance both within and between buildings and estimating neighbourhood size at 268 individuals. These findings indicate the scale required to suppress local outbreaks of arboviral disease and to target releases of modified mosquitoes for mosquito and disease control. Our methodology is readily implementable for studies of other species, including pests and species of conservation significance.
    Matched MeSH terms: Computational Biology/methods*
  11. Wilting A, Cord A, Hearn AJ, Hesse D, Mohamed A, Traeholdt C, et al.
    PLoS One, 2010;5(3):e9612.
    PMID: 20305809 DOI: 10.1371/journal.pone.0009612
    The flat-headed cat (Prionailurus planiceps) is one of the world's least known, highly threatened felids with a distribution restricted to tropical lowland rainforests in Peninsular Thailand/Malaysia, Borneo and Sumatra. Throughout its geographic range large-scale anthropogenic transformation processes, including the pollution of fresh-water river systems and landscape fragmentation, raise concerns regarding its conservation status. Despite an increasing number of camera-trapping field surveys for carnivores in South-East Asia during the past two decades, few of these studies recorded the flat-headed cat.
    Matched MeSH terms: Computational Biology/methods
  12. Loh SY, Jahans-Price T, Greenwood MP, Greenwood M, Hoe SZ, Konopacka A, et al.
    eNeuro, 2017 12 21;4(6).
    PMID: 29279858 DOI: 10.1523/ENEURO.0243-17.2017
    The supraoptic nucleus (SON) is a group of neurons in the hypothalamus responsible for the synthesis and secretion of the peptide hormones vasopressin and oxytocin. Following physiological cues, such as dehydration, salt-loading and lactation, the SON undergoes a function related plasticity that we have previously described in the rat at the transcriptome level. Using the unsupervised graphical lasso (Glasso) algorithm, we reconstructed a putative network from 500 plastic SON genes in which genes are the nodes and the edges are the inferred interactions. The most active nodal gene identified within the network was Caprin2. Caprin2 encodes an RNA-binding protein that we have previously shown to be vital for the functioning of osmoregulatory neuroendocrine neurons in the SON of the rat hypothalamus. To test the validity of the Glasso network, we either overexpressed or knocked down Caprin2 transcripts in differentiated rat pheochromocytoma PC12 cells and showed that these manipulations had significant opposite effects on the levels of putative target mRNAs. These studies suggest that the predicative power of the Glasso algorithm within an in vivo system is accurate, and identifies biological targets that may be important to the functional plasticity of the SON.
    Matched MeSH terms: Computational Biology/methods*
  13. Mohd Salleh F, Ramos-Madrigal J, Peñaloza F, Liu S, Mikkel-Holger SS, Riddhi PP, et al.
    Gigascience, 2017 08 01;6(8):1-8.
    PMID: 28873965 DOI: 10.1093/gigascience/gix053
    Southeast (SE) Asia is 1 of the most biodiverse regions in the world, and it holds approximately 20% of all mammal species. Despite this, the majority of SE Asia's genetic diversity is still poorly characterized. The growing interest in using environmental DNA to assess and monitor SE Asian species, in particular threatened mammals-has created the urgent need to expand the available reference database of mitochondrial barcode and complete mitogenome sequences. We have partially addressed this need by generating 72 new mitogenome sequences reconstructed from DNA isolated from a range of historical and modern tissue samples. Approximately 55 gigabases of raw sequence were generated. From this data, we assembled 72 complete mitogenome sequences, with an average depth of coverage of ×102.9 and ×55.2 for modern samples and historical samples, respectively. This dataset represents 52 species, of which 30 species had no previous mitogenome data available. The mitogenomes were geotagged to their sampling location, where known, to display a detailed geographical distribution of the species. Our new database of 52 taxa will strongly enhance the utility of environmental DNA approaches for monitoring mammals in SE Asia as it greatly increases the likelihoods that identification of metabarcoding sequencing reads can be assigned to reference sequences. This magnifies the confidence in species detections and thus allows more robust surveys and monitoring programmes of SE Asia's threatened mammal biodiversity. The extensive collections of historical samples from SE Asia in western and SE Asian museums should serve as additional valuable material to further enrich this reference database.
    Matched MeSH terms: Computational Biology/methods
  14. da Fonseca RR, Couto A, Machado AM, Brejova B, Albertin CB, Silva F, et al.
    Gigascience, 2020 Jan 01;9(1).
    PMID: 31942620 DOI: 10.1093/gigascience/giz152
    BACKGROUND: The giant squid (Architeuthis dux; Steenstrup, 1857) is an enigmatic giant mollusc with a circumglobal distribution in the deep ocean, except in the high Arctic and Antarctic waters. The elusiveness of the species makes it difficult to study. Thus, having a genome assembled for this deep-sea-dwelling species will allow several pending evolutionary questions to be unlocked.

    FINDINGS: We present a draft genome assembly that includes 200 Gb of Illumina reads, 4 Gb of Moleculo synthetic long reads, and 108 Gb of Chicago libraries, with a final size matching the estimated genome size of 2.7 Gb, and a scaffold N50 of 4.8 Mb. We also present an alternative assembly including 27 Gb raw reads generated using the Pacific Biosciences platform. In addition, we sequenced the proteome of the same individual and RNA from 3 different tissue types from 3 other species of squid (Onychoteuthis banksii, Dosidicus gigas, and Sthenoteuthis oualaniensis) to assist genome annotation. We annotated 33,406 protein-coding genes supported by evidence, and the genome completeness estimated by BUSCO reached 92%. Repetitive regions cover 49.17% of the genome.

    CONCLUSIONS: This annotated draft genome of A. dux provides a critical resource to investigate the unique traits of this species, including its gigantism and key adaptations to deep-sea environments.

    Matched MeSH terms: Computational Biology/methods
  15. Wei K, Sutherland H, Camilleri E, Haupt LM, Griffiths LR, Gan SH
    Mol Biol Rep, 2014 Dec;41(12):8285-92.
    PMID: 25213548 DOI: 10.1007/s11033-014-3729-x
    Computational epigenetics is a new area of research focused on exploring how DNA methylation patterns affect transcription factor binding that affect gene expression patterns. The aim of this study was to produce a new protocol for the detection of DNA methylation patterns using computational analysis which can be further confirmed by bisulfite PCR with serial pyrosequencing. The upstream regulatory element and pre-initiation complex relative to CpG islets within the methylenetetrahydrofolate reductase gene were determined via computational analysis and online databases. The 1,104 bp long CpG island located near to or at the alternative promoter site of methylenetetrahydrofolate reductase gene was identified. The CpG plot indicated that CpG islets A and B, within the island, contained 62 and 75 % GC content CpG ratios of 0.70 and 0.80-0.95, respectively. Further exploration of the CpG islets A and B indicates that the transcription start sites were GGC which were absent from the TATA boxes. In addition, although six PROSITE motifs were identified in CpG B, no motifs were detected in CpG A. A number of cis-regulatory elements were found in different regions within the CpGs A and B. Transcription factors were predicted to bind to CpGs A and B with varying affinities depending on the DNA methylation status. In addition, transcription factor binding may influence the expression patterns of the methylenetetrahydrofolate reductase gene by recruiting chromatin condensation inducing factors. These results have significant implications for the understanding of the architecture of transcription factor binding at CpG islets as well as DNA methylation patterns that affect chromatin structure.
    Matched MeSH terms: Computational Biology/methods*
  16. Saleh MA, Solayman M, Paul S, Saha M, Khalil MI, Gan SH
    Biomed Res Int, 2016;2016:9142190.
    PMID: 27294143 DOI: 10.1155/2016/9142190
    Despite the reported association of adiponectin receptor 1 (ADIPOR1) gene mutations with vulnerability to several human metabolic diseases, there is lack of computational analysis on the functional and structural impacts of single nucleotide polymorphisms (SNPs) of the human ADIPOR1 at protein level. Therefore, sequence- and structure-based computational tools were employed in this study to functionally and structurally characterize the coding nsSNPs of ADIPOR1 gene listed in the dbSNP database. Our in silico analysis by SIFT, nsSNPAnalyzer, PolyPhen-2, Fathmm, I-Mutant 2.0, SNPs&GO, PhD-SNP, PANTHER, and SNPeffect tools identified the nsSNPs with distorting functional impacts, namely, rs765425383 (A348G), rs752071352 (H341Y), rs759555652 (R324L), rs200326086 (L224F), and rs766267373 (L143P) from 74 nsSNPs of ADIPOR1 gene. Finally the aforementioned five deleterious nsSNPs were introduced using Swiss-PDB Viewer package within the X-ray crystal structure of ADIPOR1 protein, and changes in free energy for these mutations were computed. Although increased free energy was observed for all the mutants, the nsSNP H341Y caused the highest energy increase amongst all. RMSD and TM scores predicted that mutants were structurally similar to wild type protein. Our analyses suggested that the aforementioned variants especially H341Y could directly or indirectly destabilize the amino acid interactions and hydrogen bonding networks of ADIPOR1.
    Matched MeSH terms: Computational Biology/methods*
  17. Yan CZY, Austin CM, Ayub Q, Rahman S, Gan HM
    FEMS Microbiol Lett, 2019 09 01;366(17).
    PMID: 31589302 DOI: 10.1093/femsle/fnz211
    The Malaysian and global shrimp aquaculture production has been significantly impacted by acute hepatopancreatic necrosis disease (AHPND) typically caused by Vibrio parahaemolyticus harboring the pVA plasmid containing the pirAVp and pirBVp genes, which code for Photorhabdus insect-related (Pir) toxin. The limited genomic resource for V. parahaemolyticus strains from Malaysian aquaculture farms precludes an in-depth understanding of their diversity and evolutionary relationships. In this study, we isolated shrimp-associated and environmental (rearing water) V. parahaemolyticus from three aquaculture farms located in Northern and Central Malaysia followed by whole-genome sequencing of 40 randomly selected isolates on the Illumina MiSeq. Phylogenomic analysis and multilocus sequence typing (MLST) reveal distinct lineages of V. parahaemolyticus that harbor the pirABVp genes. The recovery of pVA plasmid backbone devoid of pirAVp or pirABVp in some V. parahaemolyticus isolates suggests that the toxin genes are prone to deletion. The new insight gained from phylogenomic analysis of Asian V. parahaemolyticus, in addition to the observed genomic instability of pVa plasmid, will have implications for improvements in aquaculture practices to diagnose, treat or limit the impacts of this disease.
    Matched MeSH terms: Computational Biology/methods
  18. Mat-Sharani S, Firdaus-Raih M
    BMC Bioinformatics, 2019 Feb 04;19(Suppl 13):551.
    PMID: 30717662 DOI: 10.1186/s12859-018-2550-2
    BACKGROUND: Small open reading frames (smORF/sORFs) that encode short protein sequences are often overlooked during the standard gene prediction process thus leading to many sORFs being left undiscovered and/or misannotated. For many genomes, a second round of sORF targeted gene prediction can complement the existing annotation. In this study, we specifically targeted the identification of ORFs encoding for 80 amino acid residues or less from 31 fungal genomes. We then compared the predicted sORFs and analysed those that are highly conserved among the genomes.

    RESULTS: A first set of sORFs was identified from existing annotations that fitted the maximum of 80 residues criterion. A second set was predicted using parameters that specifically searched for ORF candidates of 80 codons or less in the exonic, intronic and intergenic sequences of the subject genomes. A total of 1986 conserved sORFs were predicted and characterized.

    CONCLUSIONS: It is evident that numerous open reading frames that could potentially encode for polypeptides consisting of 80 amino acid residues or less are overlooked during standard gene prediction and annotation. From our results, additional targeted reannotation of genomes is clearly able to complement standard genome annotation to identify sORFs. Due to the lack of, and limitations with experimental validation, we propose that a simple conservation analysis can provide an acceptable means of ensuring that the predicted sORFs are sufficiently clear of gene prediction artefacts.

    Matched MeSH terms: Computational Biology/methods*
  19. Horne HN, Chung CC, Zhang H, Yu K, Prokunina-Olsson L, Michailidou K, et al.
    PLoS One, 2016;11(8):e0160316.
    PMID: 27556229 DOI: 10.1371/journal.pone.0160316
    The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799-121,481,132) flanking rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2: 120,300,000-120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Per-allelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry-specific principal components. The strongest association observed was with the original identified index SNP rs11249433 (minor allele frequency (MAF) 0.402; per-allele odds ratio (OR) = 1.10, 95% confidence interval (CI) 1.08-1.13, P = 1.49 x 10-21). The association for rs11249433 was limited to ER-positive breast cancers (test for heterogeneity P≤8.41 x 10-5). Additional analyses by other tumor characteristics showed stronger associations with moderately/well differentiated tumors and tumors of lobular histology. Although no significant eQTL associations were observed, in silico analyses showed that rs11249433 was located in a region that is likely a weak enhancer/promoter. Fine-mapping analysis of the 1p11.2 breast cancer susceptibility locus confirms this region to be limited to risk to cancers that are ER-positive.
    Matched MeSH terms: Computational Biology/methods
  20. Sharko F, Rbbani G, Siriyappagouder P, Raeymaekers JAM, Galindo-Villegas J, Nedoluzhko A, et al.
    BMC Bioinformatics, 2023 May 19;24(1):205.
    PMID: 37208611 DOI: 10.1186/s12859-023-05331-y
    BACKGROUND: Circular RNAs (circRNAs) are covalently closed-loop RNAs with critical regulatory roles in cells. Tens of thousands of circRNAs have been unveiled due to the recent advances in high throughput RNA sequencing technologies and bioinformatic tools development. At the same time, polymerase chain reaction (PCR) cross-validation for circRNAs predicted by bioinformatic tools remains an essential part of any circRNA study before publication.

    RESULTS: Here, we present the CircPrime web-based platform, providing a user-friendly solution for DNA primer design and thermocycling conditions for circRNA identification with routine PCR methods.

    CONCLUSIONS: User-friendly CircPrime web platform ( http://circprime.elgene.net/ ) works with outputs of the most popular bioinformatic predictors of circRNAs to design specific circular RNA primers. CircPrime works with circRNA coordinates and any reference genome from the National Center for Biotechnology Information database).

    Matched MeSH terms: Computational Biology/methods
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