Data_Sheet_1_Consistency and stability of individualized cortical functional networks parcellation at 3.0 T and 5.0 T MRI.docx by Minhua Yu (13211703)

“…The individualized cortical functional networks was parcellated for each subject using a previously proposed iteration algorithm. …”

Table_2_Meta-analysis of structural and functional brain abnormalities in schizophrenia with persistent negative symptoms using activation likelihood estimation.docx by Tingting Zhu (334564)

“…Afterward, we conducted a coordinate-based meta-analysis by using the activation likelihood estimation algorithm.</p>Results<p>Twenty-five structural MRI studies and thirty-two functional MRI studies were included in the meta-analyses. …”

Table_1_Meta-analysis of structural and functional brain abnormalities in schizophrenia with persistent negative symptoms using activation likelihood estimation.docx by Tingting Zhu (334564)

“…Afterward, we conducted a coordinate-based meta-analysis by using the activation likelihood estimation algorithm.</p>Results<p>Twenty-five structural MRI studies and thirty-two functional MRI studies were included in the meta-analyses. …”

Fig 12 - by Nisha Yadav (366131)

Data_Sheet_1_Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).docx by Niklas Pallast (6796196)

“…Following a modular structure developed in Python scripting language, the pipeline integrates established and newly developed algorithms. …”

Data_Sheet_2_Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).pdf by Niklas Pallast (6796196)

“…Following a modular structure developed in Python scripting language, the pipeline integrates established and newly developed algorithms. …”

metropolis_hastings.py;postprocessing.py;folkman_a_b_c_time.py;figures_Inverse_Proliferation.R;README.md from Bayesian inference of a non-local proliferation model by Zuzanna Szymańska (11679819)

“…;Auxiliary R (version 3.6.2) code to generate figures presenting the results of the random walk Metropolis-Hastings algorithm for the Bayesian inference of a non-local proliferation function.…”

Full Counting Statistics of Phonon Thermal Transport for Disordered Systems by Chao Zhang (9218868)

Comparison of protein coding genes differentially expressed in Stage 1 and Stage 2 blood (padj < 0.05). by Peter Nambala (7245215)

S4 Fig - by Peter Nambala (7245215)

DEGs and network analysis in Stage 1 case blood. by Peter Nambala (7245215)

Principal component analysis (PCA) of sub-layer mean intensities. by Maëlle Vilbert (17101954)

DEGs and network analysis in blood from Stage 2 case versus healthy controls. by Peter Nambala (7245215)

Data pre-processing and identification of DEGs. by Ziyang Liu (242055)

Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1 by Robert Zomer (12796235)

Data_Sheet_1_Using support vector machine to explore the difference of function connection between deficit and non-deficit schizophrenia based on gray matter volume.docx by Wenjing Zhu (487218)

“…This study aimed to investigate the alterations of functional connectivity between DS and NDS based on the ROI obtained by machine learning algorithms and differential GMV. …”

GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios by Yang Lan (20927512)

“…Using occurrence data and environmental variable, we employ the Maximum Entropy (MaxEnt) algorithm within the species distribution modeling (SDM) framework to estimate occurrence probability at a spatial resolution of 1/12° (~10 km). …”

Table_1_The Impact of Spatial Normalization Strategies on the Temporal Features of the Resting-State Functional MRI: Spatial Normalization Before rs-fMRI Features Calculation May R... by Zhao Qing (8041313)

“…We hypothesized that calculating the rs-fMRI features, for example, functional connectivity (FC), regional homogeneity (ReHo), or amplitude of low-frequency fluctuation (ALFF) in individual space, before the spatial normalization (referred to as “Postnorm”) can be an improvement to avoid artifacts and increase the results’ reliability. …”

SpatialKNifeY analysis landscape. by Shunsuke A. Sakai (13789939)

Data_Sheet_5_Decreased default mode network functional connectivity with visual processing regions as potential biomarkers for delayed neurocognitive recovery: A resting-state fMRI... by Zhaoshun Jiang (7478243)

“…Objectives<p>The abnormal functional connectivity (FC) pattern of default mode network (DMN) may be key markers for early identification of various cognitive disorders. …”