MitoDEGs in DCM. by Wenlong Kuang (20485167)

Construction of weighted co-expression network related datasets and identification of related key modules. by Wenlong Kuang (20485167)

Free energy landscape projections for selected conformations. by Samuel Eriksson Lidbrink (21616146)

M2 spread and upper ECD spread for the reruns. by Samuel Eriksson Lidbrink (21616146)

Oryza australiensis species-specific gene and protein candidates by Sabrina Morrison (19846869)

“…</p><p dir="ltr">The protein sequence data for both <i>O. australiensis</i> and <i>O. sativa</i> (Osativa323v7 protein file Phytozome). were filtered for the longest isomer and then analysed for orthologous and unique protein clusters within the O. australiensis genome using OrthoVenn3 (parameters: OrthoFinder algorithm, E-value: 1e-2, Inflation value:1.50) (Sun et al., 2023, Emms and Kelly, 2019). …”

Finding the most diverse subset of proteins - Genome Informatics 2024 by Amanda Clare (98717)

“…It would be useful to discover the possible space of proteins for a given functional role. How could a protein be modified? …”

Features of 13 pSRGs obtained by machine learning methods. by Xihao Shen (20347942)

Alignment of TSPANs in <i>Entamoeba histolytica</i>. by Han Jiang (195350)

Partial amino acids sequence alignment between <i>Dd</i>interaptin and <i>Eh</i>interaptin and Coiled-coil (CC) structure prediction for <i>Eh</i>interaptin (EHI_148910). by Han Jiang (195350)

Overview diagram of the method and contributions of this work. by Gowri Nayar (14234462)

“…We implement our attention analysis algorithm (described in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013424#sec005" target="_blank">Sect 2.2</a>) to obtain a set of HA sites for each protein. …”

Analysis of PPI network and hub genes. by Yubin Xue (1537042)

Amino acid sequence analysis of pB169L. by Jiaqi Li (220961)

4sU-seq Signal at Putative Enhancers in Day 3 and 4 ADE Populations. by Jurriaan Jochem Hölzenspies (20642889)

Functional and Structural Characterization of Mechanosensitive Piezo1 Channel in Disease by Sophia Liu (722004)

“…However, most algorithms struggled to distinguish gain-of-function (GoF) from loss-of-function (LoF) variants, with GoF variants showing lower pathogenicity scores despite clinical relevance.…”

Data generation process. by Nicola Dietler (12551766)

Table 6_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”

Table 7_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”

Table 3_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”

Table 2_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”

Table 1_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”