搜索结果：DNA research : an international journal for rapid publication of reports on genes and genomes

The advent of rapid and inexpensive DNA sequencing has led to an explosion of data waiting to be transformed into knowledge about genome organization and function. Gene prediction is customarily the starting point for genome analysis. This paper presents a bioinformatics study of the oil palm genome, including comparative genomics analysis, database and tools development, and mining of biological data for genes of interest. We have annotated 26,059 oil palm genes integrated from two independent gene-prediction pipelines, Fgenesh++ and Seqping. This integrated annotation constitutes a significant improvement in comparison to the preliminary annotation published in 2013. We conducted a comprehensive analysis of intronless, resistance and fatty acid biosynthesis genes, and demonstrated that the high quality of the current genome annotation. 3,658 intronless genes were identified in the oil palm genome, an important resource for evolutionary study. Further analysis of the oil palm genes revealed 210 candidate resistance genes involved in pathogen defense. Fatty acids have diverse applications ranging from food to industrial feedstocks, and we identified 42 key genes involved in fatty a

An exploratory, descriptive analysis is presented of the national orientation of scientific, scholarly journals as reflected in the affiliations of publishing or citing authors. It calculates for journals covered in Scopus an Index of National Orientation (INO), and analyses the distribution of INO values across disciplines and countries, and the correlation between INO values and journal impact factors. The study did not find solid evidence that journal impact factors are good measures of journal internationality in terms of the geographical distribution of publishing or citing authors, as the relationship between a journal's national orientation and its citation impact is found to be inverse U-shaped. In addition, journals publishing in English are not necessarily internationally oriented in terms of the affiliations of publishing or citing authors; in social sciences and humanities also USA has their nationally oriented literatures. The paper examines the extent to which nationally oriented journals entering Scopus in earlier years, have become in recent years more international. It is found that in the study set about 40 per cent of such journals does reveal traces of internati

We have developed a (freeware) routine for "referenced publication years spectroscopy" (RPYS) and apply this method to the historiography of "iMetrics," that is, the junction of the journals Scientometrics, Informetrics, and the relevant subset of JASIST (approx. 20%) that shapes the intellectual space for the development of information metrics (bibliometrics, scientometrics, informetrics, and webometrics). The application to information metrics (our own field of research) provides us with the opportunity to validate this methodology, and to add a reflection about using citations for the historical reconstruction. The results show that the field is rooted in individual contributions of the 1920s-1950s (e.g., Alfred J. Lotka), and was then shaped intellectually in the early 1960s by a confluence of the history of science (Derek de Solla Price), documentation (e.g., Michael M. Kessler's "bibliographic coupling"), and "citation indexing" (Eugene Garfield). Institutional development at the interfaces between science studies and information science has been reinforced by the new journal Informetrics since 2007. In a concluding reflection, we return to the question of how the historiogra

Capturing the physical organisation and dynamics of genomic regions is one of the major open challenges in biology. The kinetoplast DNA (kDNA) is a topologically complex genome, made by thousands of DNA (mini and maxi) circles interlinked into a two-dimensional Olympic network. The organisation and dynamics of these DNA circles are poorly understood. In this paper, we show that dCas9 linked to Quantum Dots can efficiently label different classes of DNA minicircles in kDNA. We use this method to study the distribution and dynamics of different classes of DNA minicircles within the network. We discover that maxicircles display a preference to localise at the periphery of the network and that they undergo subdiffusive dynamics. From the latter, we can also quantify the effective network stiffness, confirming previous indirect estimations via AFM. Our method could be used more generally, to quantify the location, dynamics and material properties of genomic regions in other complex genomes, such as that of bacteria, and to study their behaviour in the presence of DNA-binding proteins.

Animal mitochondrial genomes usually have two transfer RNAs for Leucine: one, with anticodon UAG, translates the four-codon family CUN, whilst the other, with anticodon UAA, translates the two-codon family UUR. These two genes must differ at the third anticodon position, but in some species the genes differ at many additional sites, indicating that these genes have been independent for a long time. Duplication and deletion of genes in mitochondrial genomes occurs frequently during the evolution of the Metazoa. If a tRNA-Leu gene were duplicated and a substitution occurred in the anticodon, this would effectively turn one type of tRNA into the other. The original copy of the second tRNA type might then be lost by a deletion elsewhere in the genome. There are several groups of species in which the two tRNA-Leu genes occur next to one another (or very close) on the genome, which suggests that tandem duplication has occurred. Here we use RNA-specific phylogenetic methods to determine evolutionary trees for both genes. We present evidence that the process of duplication, anticodon mutation and deletion of tRNA-Leu genes has occurred at least five times during the evolution of the Metazo

Publication patterns of 79 forest scientists awarded major international forestry prizes during 1990-2010 were compared with the journal classification and ranking promoted as part of the 'Excellence in Research for Australia' (ERA) by the Australian Research Council. The data revealed that these scientists exhibited an elite publication performance during the decade before and two decades following their first major award. An analysis of their 1703 articles in 431 journals revealed substantial differences between the journal choices of these elite scientists and the ERA classification and ranking of journals. Implications from these findings are that additional cross-classifications should be added for many journals, and there should be an adjustment to the ranking of several journals relevant to the ERA Field of Research classified as 0705 Forestry Sciences.

DNA methylation is a well-studied genetic modification crucial to regulate the functioning of the genome. Its alterations play an important role in tumorigenesis and tumor-suppression. Thus, studying DNA methylation data may help biomarker discovery in cancer. Since public data on DNA methylation become abundant, and considering the high number of methylated sites (features) present in the genome, it is important to have a method for efficiently processing such large datasets. Relying on big data technologies, we propose BIGBIOCL an algorithm that can apply supervised classification methods to datasets with hundreds of thousands of features. It is designed for the extraction of alternative and equivalent classification models through iterative deletion of selected features. We run experiments on DNA methylation datasets extracted from The Cancer Genome Atlas, focusing on three tumor types: breast, kidney, and thyroid carcinomas. We perform classifications extracting several methylated sites and their associated genes with accurate performance. Results suggest that BIGBIOCL can perform hundreds of classification iterations on hundreds of thousands of features in few hours. Moreover,

Machine learning (ML) has emerged as a prominent field of research in computer science and other related fields, thereby driving advancements in other domains of interest. As the field continues to evolve, it is crucial to understand the landscape of highly cited publications to identify key trends, influential authors, and significant contributions made thus far. In this paper, we present a comprehensive bibliometric analysis of highly cited ML publications. We collected a dataset consisting of the top-cited papers from reputable ML conferences and journals, covering a period of several years from 1959 to 2022. We employed various bibliometric techniques to analyze the data, including citation analysis, co-authorship analysis, keyword analysis, and publication trends. Our findings reveal the most influential papers, highly cited authors, and collaborative networks within the machine learning community. We identify popular research themes and uncover emerging topics that have recently gained significant attention. Furthermore, we examine the geographical distribution of highly cited publications, highlighting the dominance of certain countries in ML research. By shedding light on t

DNA methylation can function as a toxic alkylation reaction exploited by chemotherapeutic agents to induce cancer cell death. However, finely tuned DNA methylation plays a fundamental role in cellular physiology, particularly in the epigenetic regulation of gene expression. Once thought to act solely as a repressor of gene transcription, its functional role has since been elucidated as genomic locus-specific and deeply connected with other epigenetic factors. Following the clinical approval of DNA methyltransferase inhibitors, such as Azacitidine and Decitabine, for the treatment of haematological malignancies, considerable efforts have been devoted to developing pharmacological tools that modulate epigenetic DNA methylation. However, the lack of gene selectivity in these agents limits their therapeutic efficacy and increases off-target toxicity. Moreover, the non-gene-selective nature of current DNA methylation-targeting molecules fails to meet the standards required to discern the nuanced roles of DNA methylation across diverse pathophysiological contexts and genomic loci, particularly in an era where next-generation sequencing and omics technologies enable hi ghresolution epigen

The proton-magnetic reaction is commonly used in MRI machines with a strong magnetic field of over 1 T, while this study hypothesized that the electron magnetic reaction of hydrogen could affect the hydrogen bonds of double-stranded DNA (dsDNA) at a low magnetic field below 0.01 T. The goal is to develop a hydrogen bonding magnetic reaction-based gene regulation (HBMR-GR) system. The polarities of DNA base pairs are derived from the relative electrostatic charge between purines and pyrimidines, which become positively and negatively charged, respectively. The Pyu dsDNAs with pyrimidine(s)-purine(s) sequences, ds3T3A, ds3C3G, and ds3C3A, showed stronger DNA hybridization potential, increased infrared absorption at 3400-3200 cm-1, and a unique DNA conformation in HPLC analysis compared to the corresponding Puy dsDNAs. To target the three-dimensional structure of dsDNA based on the DNA base pair polarities, one can use cyclic electromagnetic DNA simulation (CEDS) with approximately 25% efficiency for randomly oriented dsDNAs. CEDS was found to induce sequence-specific hybridization of target oligo-dsDNAs in 0.005M NaCl solution and sequence-specific conformation of oligo-dsDNAs in 0.1

We present a Compression Tool, "GenBit Compress", for genetic sequences based on our new proposed "GenBit Compress Algorithm". Our Tool achieves the best compression ratios for Entire Genome (DNA sequences) . Significantly better compression results show that GenBit compress algorithm is the best among the remaining Genome compression algorithms for non-repetitive DNA sequences in Genomes. The standard Compression algorithms such as gzip or compress cannot compress DNA sequences but only expand them in size. In this paper we consider the problem of DNA compression. It is well known that one of the main features of DNA Sequences is that they contain substrings which are duplicated except for a few random Mutations. For this reason most DNA compressors work by searching and encoding approximate repeats. We depart from this strategy by searching and encoding only exact repeats. our proposed algorithm achieves the best compression ratio for DNA sequences for larger genome. As long as 8 lakh characters can be given as input While achieving the best compression ratios for DNA sequences, our new GenBit Compress program significantly improves the running time of all previous DNA compressor

Conference publications in computer science (CS) have attracted scholarly attention due to their unique status as a main research outlet unlike other science fields where journals are dominantly used for communicating research findings. One frequent research question has been how different conference and journal publications are, considering a paper as a unit of analysis. This study takes an author-based approach to analyze publishing patterns of 517,763 scholars who have ever published both in CS conferences and journals for the last 57 years, as recorded in DBLP. The analysis shows that the majority of CS scholars tend to make their scholarly debut, publish more papers, and collaborate with more coauthors in conferences than in journals. Importantly, conference papers seem to serve as a distinct channel of scholarly communication, not a mere preceding step to journal publications: coauthors and title words of authors across conferences and journals tend not to overlap much. This study corroborates findings of previous studies on this topic from a distinctive perspective and suggests that conference authorship in CS calls for more special attention from scholars and administrators

Reflexive metrics is a branch of science studies which explores how the demand for accountability and performance measurement in science has shaped the research culture in recent decades. Hypercompetition and publication pressure are part of this neoliberal culture. How do scientists respond to these pressures? Studies on research integrity and organizational culture suggest that people who feel treated unfairly by their institution are more likely to engage in deviant behaviour, such as scientific misconduct. By building up on reflexive metrics, combined with studies on the influence of organisational culture on research integrity, this study reflects on the research behaviour of astronomers: 1) To what extent is research (mis-)behaviour reflexive, i.e. dependent on perceptions of publication pressure and distributive & organisational justice? 2) What impact does scientific misconduct have on research quality? In order to perform this reflection, we conducted a comprehensive survey of academic and non-academic astronomers worldwide and received 3,509 responses. We found that publication pressure explains 19% of the variance in occurrence of misconduct and between 7 and 13% of

In eukaryotic genes the protein coding sequence is split into several fragments, the exons, separated by non-coding DNA stretches, the introns. Prokaryotes do not have introns in their genome. We report the calculations of stability domains of actin genes for various organisms in the animal, plant and fungi kingdoms. Actin genes have been chosen because they have been highly conserved during evolution. In these genes all introns were removed so as to mimic ancient genes at the time of the early eukaryotic development, i.e. before introns insertion. Common stability boundaries are found in evolutionary distant organisms, which implies that these boundaries date from the early origin of eukaryotes. In general boundaries correspond with introns positions of vertebrates and other animals actins, but not much for plants and fungi. The sharpest boundary is found in a locus where fungi, algae and animals have introns in positions separated by one nucleotide only, which identifies a hot-spot for insertion. These results suggest that some introns may have been incorporated into the genomes through a thermodynamic driven mechanism, in agreement with previous observations on human genes. They

Because genomes are products of natural processes rather than intelligent design, all genomes contain functional and nonfunctional parts. The fraction of the genome that has no biological function is called rubbish DNA. Rubbish DNA consists of junk DNA, i.e., the fraction of the genome on which selection does not operate, and garbage DNA, i.e., sequences that lower the fitness of the organism, but exist in the genome because purifying selection is neither omnipotent nor instantaneous. In this chapter, I (1) review the concepts of genomic function and functionlessness from an evolutionary perspective, (2) present a precise nomenclature of genomic function, (3) discuss the evidence for the existence of vast quantities of junk DNA within the human genome, (4) discuss the mutational mechanisms responsible for generating junk DNA, (5) spell out the necessary evolutionary conditions for maintaining junk DNA, (6) outline various methodologies for estimating the functional fraction within the genome, and (7) present a recent estimate for the functional fraction of our genome.

Webology is an international peer-reviewed journal in English devoted to the field of the World Wide Web and serves as a forum for discussion and experimentation. It serves as a forum for new research in information dissemination and communication processes in general, and in the context of the World Wide Web in particular. This paper presents a Scientometric analysis of the Webology Journal. The paper analyses the pattern of growth of the research output published in the journal, pattern of authorship, author productivity, and subjects covered to the papers over the period (2013-2017). It is found that 62 papers were published during the period of study (2013-2017). The maximum numbers of articles were collaborative in nature. The subject concentration of the journal noted was Social Networking/Web 2.0/Library 2.0 and Scientometrics or Bibliometrics. Iranian researchers contributed the maximum number of articles (37.10%). The study applied standard formula and statistical tools to bring out the factual result.

DESIDOC Journal of Library & Information Technology (DJLIT) formerly known as DESIDOC Bulletin of Information Technology is a peer-reviewed, open access, bimonthly journal. This paper presents a Scientometric analysis of the DESIDOC Journal. The paper analyses the pattern of growth of the research output published in the journal, pattern of authorship, author productivity, and, subjects covered to the papers over the period (2013-2017). It is found that 227 papers were published during the period of study (2001-2012). The maximum numbers of articles were collaborative in nature. The subject concentration of the journal noted is Scientometrics. The maximum numbers of articles (65%) have ranged their thought contents between 6 and 10 pages. The study applied standard formula and statistical tools to bring out the factual result.

A number of journal classification systems have been developed in bibliometrics since the launch of the Citation Indices by the Institute of Scientific Information (ISI) in the 1960s. These systems are used to normalize citation counts with respect to field-specific citation patterns. The best known system is the so-called "Web-of-Science Subject Categories" (WCs). In other systems papers are classified by algorithmic solutions. Using the Journal Citation Reports 2014 of the Science Citation Index and the Social Science Citation Index (n of journals = 11,149), we examine options for developing a new system based on journal classifications into subject categories using aggregated journal-journal citation data. Combining routines in VOSviewer and Pajek, a tree-like classification is developed. At each level one can generate a map of science for all the journals subsumed under a category. Nine major fields are distinguished at the top level. Further decomposition of the social sciences is pursued for the sake of example with a focus on journals in information science (LIS) and science studies (STS). The new classification system improves on alternative options by avoiding the problem

The association between productivity and impact of scientific production is a long-standing debate in science that remains controversial and poorly understood. Here we present a large-scale analysis of the association between yearly publication numbers and average journal-impact metrics for the Brazilian scientific elite. We find this association to be discipline-specific, career-age dependent, and similar among researchers with outlier and non-outlier performance. Outlier researchers either outperform in productivity or journal prestige, but they rarely do so in both categories. Non-outliers also follow this trend and display negative correlations between productivity and journal prestige but with discipline-dependent intensity. Our research indicates that academics are averse to simultaneous changes in their productivity and journal-prestige levels over consecutive career years. We also find that career patterns concerning productivity and journal prestige are discipline-specific, having in common a raise of productivity with career age for most disciplines and a higher chance of outperforming in journal impact during early career stages.