<b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

“…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…”

Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

Subjects:

Functional analysis of the oral dysbiosis dataset using molecular function GO terms. by Ray Sajulga (5721518)

Identification and functional analysis of hub genes. by Wei Ya Lan (22403712)

“…(E) GO enrichment analysis of shared candidate genes, showing the top three terms for biological process (BP), cellular component (CC), and molecular function (MF).…”

GO pathways analysis results. by Fengjun Zhang (5878169)

Subjects:

GO annotation and KEGG pathway enrichment analysis of DEGs. by Ziyang Liu (242055)

Subjects:

Functional enrichment of DEGs. by Man Wang (110466)

“…</p><p>Methods</p><p>The study employed a combination of differential expression analysis, weighted gene co-expression network analysis (WGCNA), and various machine learning algorithms to screen for characteristic genes. Gene set enrichment analysis (GSEA), gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to evaluate relevant biological functions and pathways. …”

Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

Subjects:

Functional enrichment analysis of DEGs. by Huiling Deng (4427161)

Specific N-terminal signature detected in GO terms corresponding to cellular pathways and molecular function. by Salomé Nashed (16839488)

“…<p>Bar graph showing the percentages of use of the 20 amino acids at position 2 in GO terms corresponding to cellular pathways (A) and molecular functions (B) showing preferences at position 2 for specific amino acids. …”

Functional enrichment analysis of DE-FRGs. by Yan Huang (46805)

Functional enrichment and correlation analysis of hub DE-SRGs. by Xihao Shen (20347942)

Subjects: “…Cell Biology…”

Correlation between the BNA neuromarker linear scores and the mUPDRS scores. by Sharon Hassin-Baer (420354)

Subjects: “…Cell Biology…”

The BNA neuromarker characteristics. by Sharon Hassin-Baer (420354)

Subjects: “…Cell Biology…”

Features of the BNA neuromarker. by Sharon Hassin-Baer (420354)

Subjects: “…Cell Biology…”

Schematic depiction of BNA scores. by Sharon Hassin-Baer (420354)

Subjects: “…Cell Biology…”

Demographic and clinical characteristics of participants included in the BNA neuromarker. by Sharon Hassin-Baer (420354)

Subjects: “…Cell Biology…”

Results of the cognitive tasks performance. by Sharon Hassin-Baer (420354)

Subjects: “…Cell Biology…”

GO enrichment analysis of <i>MeASLBDs</i> target genes. by Yiming Mao (6059345)

Subjects:

GSVA, GO, and KEGG Enrichment Analysis After Sample Clustering and Subtyping. by Ziyang Liu (242055)

Subjects: