Listed python codes of our algorithm with explanations (Python 3.9 recommended). by Takayuki Niizato (162226)

Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

“…<div><p>Chest X-ray image classification plays an important role in medical diagnostics. Machine learning algorithms enhanced the performance of these classification algorithms by introducing advance techniques. …”

Example of landmark registration to align ‘peaks’ of high density in the probability density function (PDF) of CD4 expression on blood T cells for a target distribution and chosen... by Ross J. Burton (10941910)

Functions of genes, detected simultaneously in 3 "diseased" blocks («Prostate Disease», «PCa», «Not PCa») and missing in the "Healthy" block and one gene (HRAS), found only in the... by O. E. Bryzgunova (6577043)

Results of the application of different clustering algorithms to average functional connectivity from healthy subjects. by Francisco Páscoa dos Santos (16510676)

“…<p>A) Resulting cluster inertia from applying the k-means algorithm described in the methods to empirical averaged functional connectivity from healthy subjects, with different numbers of clusters. …”

Image 6_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.tiff by Jared Lichtarge (20548571)

“…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…”

Image 5_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.tiff by Jared Lichtarge (20548571)

“…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…”

Image 3_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.tiff by Jared Lichtarge (20548571)

“…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…”

Image 1_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.jpeg by Jared Lichtarge (20548571)

“…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…”

Image 4_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.tiff by Jared Lichtarge (20548571)

“…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…”

Image 2_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.tiff by Jared Lichtarge (20548571)

“…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…”

Data Sheet 1_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.csv by Jared Lichtarge (20548571)

“…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…”

Adaptive H-REMD simulation algorithm. by Danial Pourjafar-Dehkordi (7165523)

Genes that contribute to PCA and GO terms of enriched and differentially expressed genes. GO, gene ontology; PCA, principal component analysis. by Tomokatsu Udagawa (11675636)

Subjects:

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

Principal Component Analysis (PCA) of the independent dataset from the HPC cohort. by Erica A. K. DePasquale (11851483)

Subjects:

PCA calculation FRHGs score. by Lixia Chen (614030)

Subjects:

Loss functions between PCA-DNN model and PCA-LSTM model. by Cihun-Siyong Alex Gong (11874066)

Workflow of the BOMS algorithm. by Ocima Kamboj (21533199)

Performance of PCA and Joint Autoencoder (JAE) denoising algorithms. by Ege Altan (11768156)