
The fields of Metagenomics and Metatranscriptomics involve the examination of complete nucleotide sequences, gene identification, and analysis of potential biological functions within diverse organisms or environmental samples. Despite the vast opportunities for discovery in metagenomics, the sheer volume and complexity of sequence data often present challenges in processing analysis and visualization. This article highlights the critical role of advanced visualization tools in enabling effective exploration, querying, and analysis of these complex datasets. Emphasizing the importance of accessibility, the article categorizes various visualizers based on their intended applications and highlights their utility in empowering bioinformaticians and non-bioinformaticians to interpret and derive insights from meta-omics data effectively.
570, Numerical and Computational Mathematics, 1.1 Normal biological development and functioning, Bioinformatics and Computational Biology, Applied computing, Computation Theory and Mathematics, Biodiversity, Review Article, Biological Sciences, Ecosystems, 004, Databases, Biochemistry and cell biology, Genetics, Generic health relevance, Metagenomics, Phylogeny, Visualization tools, TP248.13-248.65, Biotechnology
570, Numerical and Computational Mathematics, 1.1 Normal biological development and functioning, Bioinformatics and Computational Biology, Applied computing, Computation Theory and Mathematics, Biodiversity, Review Article, Biological Sciences, Ecosystems, 004, Databases, Biochemistry and cell biology, Genetics, Generic health relevance, Metagenomics, Phylogeny, Visualization tools, TP248.13-248.65, Biotechnology
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 29 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
