Additional file 1: of Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimerâs disease patients

Additional file 2: of Genome-wide analysis of genetic predisposition to Alzheimerâs disease and related sex disparities

Alireza Nazarian (138539)
Anatoliy Yashin (3777034)
Alexander Kulminski (6203162)

January 2019

Detailed information about the AD-associated SNPs under analysis plan 1 (males and females).Â (XLSX ...

Additional file 3: Table S17. of Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimerâs disease

Minghui Wang (15418)
Panos Roussos (318249)
Andrew McKenzie (522240)
Xianxiao Zhou (3464498)
Yuji Kajiwara (265261)
Kristen Brennand (228552)
Gabriele De Luca (244081)
John Crary (3464492)
Patrizia Casaccia (225204)
Joseph Buxbaum (3464495)
Michelle Ehrlich (3453359)
Sam Gandy (6210)
Alison Goate (48756)
Pavel Katsel (257692)
Eric Schadt (105785)
Vahram Haroutunian (23823)
Bin Zhang (64682)

November 2016

Top 10,000 probesets ranked in association with disease traits across 19 brain regions. (XLSX 6710 k...

Additional file 3: of Genetic risk for Alzheimerâs disease is concentrated in specific macrophage and microglial transcriptional networks

Katherine Tansey (4889533)
Darren Cameron (4889530)
Matthew Hill (394308)

February 2018

Table S3. Enrichment of AD-risk variants at H3K4me1 peaks from Roadmap Epigenomics Consortium data. ...

Additional file 3: of Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimerâs disease patients

Shunian Xiang (3207645)
Zhi Huang (472377)
Tianfu Wang (733641)
Zhi Han (3490682)
Christina Yu (425912)
Dong Ni (172495)
Kun Huang (136241)
Jie Zhang (64655)

January 2019

Table S2. List of 30âAD-specific modules and 31 normal-specific modules. (XLSX 27 kb

Additional file 4: of Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimerâs disease patients

Shunian Xiang (3207645)
Zhi Huang (472377)
Tianfu Wang (733641)
Zhi Han (3490682)
Christina Yu (425912)
Dong Ni (172495)
Kun Huang (136241)
Jie Zhang (64655)

January 2019

Table S3. Enriched GO terms (p-value<0.01) of all condition-specific modules. Table S4. Enriched KEG...

Additional file 5: of Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimerâs disease patients

Shunian Xiang (3207645)
Zhi Huang (472377)
Tianfu Wang (733641)
Zhi Han (3490682)
Christina Yu (425912)
Dong Ni (172495)
Kun Huang (136241)
Jie Zhang (64655)

January 2019

Table S5. Modules with targets of specific differentially expressed TF enriched in certain pathways....

Additional file 2: of Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimerâs disease patients

Shunian Xiang (3207645)
Zhi Huang (472377)
Tianfu Wang (733641)
Zhi Han (3490682)
Christina Yu (425912)
Dong Ni (172495)
Kun Huang (136241)
Jie Zhang (64655)

January 2019

Figure S1. Boxplot of ratios of overlap between modules obtained before and after adding noise to or...

Additional file 2: of Revealing Alzheimer’s disease genes spectrum in the whole-genome by machine learning

Xiaoyan Huang (112885)
Hankui Liu (4751289)
Xinming Li (143063)
Liping Guan (420348)
Jiankang Li (773081)
Laurent Tellier (4751292)
Huanming Yang (5905)
Jian Wang (5901)
Jianguo Zhang (6482)

January 2018

335 AD-associated genes. The datasets collected from public Alzheimer’s disease databases (AlzGene) ...

Additional file 1: of Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimerâs disease

Minghui Wang (15418)
Panos Roussos (318249)
Andrew McKenzie (522240)
Xianxiao Zhou (3464498)
Yuji Kajiwara (265261)
Kristen Brennand (228552)
Gabriele De Luca (244081)
John Crary (3464492)
Patrizia Casaccia (225204)
Joseph Buxbaum (3464495)
Michelle Ehrlich (3453359)
Sam Gandy (6210)
Alison Goate (48756)
Pavel Katsel (257692)
Eric Schadt (105785)
Vahram Haroutunian (23823)
Bin Zhang (64682)

November 2016

This document contains Supplementary Tables S1â16, plus their associated legends/captions. (XLSX 6...

Additional file 2: of Genetic risk for Alzheimerâs disease is concentrated in specific macrophage and microglial transcriptional networks

Katherine Tansey (4889533)
Darren Cameron (4889530)
Matthew Hill (394308)

February 2018

Table S2. Enrichment of AD-risk variants at H3K27ac peaks from Roadmap Epigenomics Consortium data. ...

Additional file 1: of GJA1 (connexin43) is a key regulator of Alzheimer’s disease pathogenesis

Yuji Kajiwara (265261)
Erming Wang (110480)
Minghui Wang (15418)
Wun Sin (6113147)
Kristen J. Brennand (6113150)
Eric Schadt (105785)
Christian Naus (6113159)
Joseph Buxbaum (3464495)
Bin Zhang (64682)

December 2018

Tables S1. Clinical and pathological traits, brain regions analyzed by transcriptome profiling, and ...

Additional file 1: of Alzheimerâs disease master regulators analysis: search for potential molecular targets and drug repositioning candidates

D. Vargas (3400316)
M. De Bastiani (5444837)
E. Zimmer (5444834)
F. Klamt (5444840)

June 2018

Figure S1. Methodology flowchart. (A) Publicly available expression profile from Gene Expression Omn...

Additional file 1: of Genetic risk for Alzheimerâs disease is concentrated in specific macrophage and microglial transcriptional networks

Katherine Tansey (4889533)
Darren Cameron (4889530)
Matthew Hill (394308)

February 2018

Table S1. Enrichment of AD-risk variants at DHSs from Roadmap Epigenomics Consortium data. (XLSX 36 ...

Additional file 1: of Identification and therapeutic modulation of a pro-inflammatory subset of disease-associated-microglia in Alzheimerâs disease

Srikant Rangaraju (4174204)
Eric Dammer (4174213)
Syed Raza (4174210)
Priyadharshini Rathakrishnan (5245535)
Hailian Xiao (36120)
Tianwen Gao (262800)
Duc Duong (4174198)
Michael Pennington (1343655)
James Lah (3504050)
Nicholas Seyfried (3504065)
Allan Levey (3504062)

May 2018

Table S1. Mouse microglial transcriptomic modules identified by Weighted Correlation Network Analysi...

Additional file 2: of Alzheimerâs disease master regulators analysis: search for potential molecular targets and drug repositioning candidates

D. Vargas (3400316)
M. De Bastiani (5444837)
E. Zimmer (5444834)
F. Klamt (5444840)

June 2018

Table S1. Hippocampus transcription factor-centered network nodes and edges information. (XLSX 40 kb

Additional file 2: of Genome-wide analysis of genetic predisposition to Alzheimerâs disease and related sex disparities

Alireza Nazarian (138539)
Anatoliy Yashin (3777034)
Alexander Kulminski (6203162)

January 2019

Detailed information about the AD-associated SNPs under analysis plan 1 (males and females).Â (XLSX ...

Additional file 3: Table S17. of Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimerâs disease

Minghui Wang (15418)
Panos Roussos (318249)
Andrew McKenzie (522240)
Xianxiao Zhou (3464498)
Yuji Kajiwara (265261)
Kristen Brennand (228552)
Gabriele De Luca (244081)
John Crary (3464492)
Patrizia Casaccia (225204)
Joseph Buxbaum (3464495)
Michelle Ehrlich (3453359)
Sam Gandy (6210)
Alison Goate (48756)
Pavel Katsel (257692)
Eric Schadt (105785)
Vahram Haroutunian (23823)
Bin Zhang (64682)

November 2016

Top 10,000 probesets ranked in association with disease traits across 19 brain regions. (XLSX 6710 k...

Additional file 3: of Genetic risk for Alzheimerâs disease is concentrated in specific macrophage and microglial transcriptional networks

Katherine Tansey (4889533)
Darren Cameron (4889530)
Matthew Hill (394308)

February 2018

Table S3. Enrichment of AD-risk variants at H3K4me1 peaks from Roadmap Epigenomics Consortium data. ...

Additional file 3: of Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimerâs disease patients

Shunian Xiang (3207645)
Zhi Huang (472377)
Tianfu Wang (733641)
Zhi Han (3490682)
Christina Yu (425912)
Dong Ni (172495)
Kun Huang (136241)
Jie Zhang (64655)

January 2019

Table S2. List of 30âAD-specific modules and 31 normal-specific modules. (XLSX 27 kb

Additional file 4: of Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimerâs disease patients

Shunian Xiang (3207645)
Zhi Huang (472377)
Tianfu Wang (733641)
Zhi Han (3490682)
Christina Yu (425912)
Dong Ni (172495)
Kun Huang (136241)
Jie Zhang (64655)

January 2019

Table S3. Enriched GO terms (p-value<0.01) of all condition-specific modules. Table S4. Enriched KEG...

Additional file 5: of Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimerâs disease patients

Shunian Xiang (3207645)
Zhi Huang (472377)
Tianfu Wang (733641)
Zhi Han (3490682)
Christina Yu (425912)
Dong Ni (172495)
Kun Huang (136241)
Jie Zhang (64655)

January 2019

Table S5. Modules with targets of specific differentially expressed TF enriched in certain pathways....

Additional file 2: of Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimerâs disease patients

Shunian Xiang (3207645)
Zhi Huang (472377)
Tianfu Wang (733641)
Zhi Han (3490682)
Christina Yu (425912)
Dong Ni (172495)
Kun Huang (136241)
Jie Zhang (64655)

January 2019

Figure S1. Boxplot of ratios of overlap between modules obtained before and after adding noise to or...

Additional file 2: of Revealing Alzheimer’s disease genes spectrum in the whole-genome by machine learning

Xiaoyan Huang (112885)
Hankui Liu (4751289)
Xinming Li (143063)
Liping Guan (420348)
Jiankang Li (773081)
Laurent Tellier (4751292)
Huanming Yang (5905)
Jian Wang (5901)
Jianguo Zhang (6482)

January 2018

335 AD-associated genes. The datasets collected from public Alzheimer’s disease databases (AlzGene) ...

Additional file 1: of Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimerâs disease

Minghui Wang (15418)
Panos Roussos (318249)
Andrew McKenzie (522240)
Xianxiao Zhou (3464498)
Yuji Kajiwara (265261)
Kristen Brennand (228552)
Gabriele De Luca (244081)
John Crary (3464492)
Patrizia Casaccia (225204)
Joseph Buxbaum (3464495)
Michelle Ehrlich (3453359)
Sam Gandy (6210)
Alison Goate (48756)
Pavel Katsel (257692)
Eric Schadt (105785)
Vahram Haroutunian (23823)
Bin Zhang (64682)

November 2016

This document contains Supplementary Tables S1â16, plus their associated legends/captions. (XLSX 6...

Additional file 2: of Genetic risk for Alzheimerâs disease is concentrated in specific macrophage and microglial transcriptional networks

Katherine Tansey (4889533)
Darren Cameron (4889530)
Matthew Hill (394308)

February 2018

Table S2. Enrichment of AD-risk variants at H3K27ac peaks from Roadmap Epigenomics Consortium data. ...

Additional file 1: of GJA1 (connexin43) is a key regulator of Alzheimer’s disease pathogenesis

Yuji Kajiwara (265261)
Erming Wang (110480)
Minghui Wang (15418)
Wun Sin (6113147)
Kristen J. Brennand (6113150)
Eric Schadt (105785)
Christian Naus (6113159)
Joseph Buxbaum (3464495)
Bin Zhang (64682)

December 2018

Tables S1. Clinical and pathological traits, brain regions analyzed by transcriptome profiling, and ...

Additional file 1: of Alzheimerâs disease master regulators analysis: search for potential molecular targets and drug repositioning candidates

D. Vargas (3400316)
M. De Bastiani (5444837)
E. Zimmer (5444834)
F. Klamt (5444840)

June 2018

Figure S1. Methodology flowchart. (A) Publicly available expression profile from Gene Expression Omn...

Additional file 1: of Genetic risk for Alzheimerâs disease is concentrated in specific macrophage and microglial transcriptional networks

Katherine Tansey (4889533)
Darren Cameron (4889530)
Matthew Hill (394308)

February 2018

Table S1. Enrichment of AD-risk variants at DHSs from Roadmap Epigenomics Consortium data. (XLSX 36 ...

Additional file 1: of Identification and therapeutic modulation of a pro-inflammatory subset of disease-associated-microglia in Alzheimerâs disease

Srikant Rangaraju (4174204)
Eric Dammer (4174213)
Syed Raza (4174210)
Priyadharshini Rathakrishnan (5245535)
Hailian Xiao (36120)
Tianwen Gao (262800)
Duc Duong (4174198)
Michael Pennington (1343655)
James Lah (3504050)
Nicholas Seyfried (3504065)
Allan Levey (3504062)

May 2018

Table S1. Mouse microglial transcriptomic modules identified by Weighted Correlation Network Analysi...

Additional file 2: of Alzheimerâs disease master regulators analysis: search for potential molecular targets and drug repositioning candidates

D. Vargas (3400316)
M. De Bastiani (5444837)
E. Zimmer (5444834)
F. Klamt (5444840)

June 2018

Table S1. Hippocampus transcription factor-centered network nodes and edges information. (XLSX 40 kb

Additional file 2: of Genome-wide analysis of genetic predisposition to Alzheimerâs disease and related sex disparities

Alireza Nazarian (138539)
Anatoliy Yashin (3777034)
Alexander Kulminski (6203162)

January 2019

Detailed information about the AD-associated SNPs under analysis plan 1 (males and females).Â (XLSX ...

Additional file 3: Table S17. of Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimerâs disease

Minghui Wang (15418)
Panos Roussos (318249)
Andrew McKenzie (522240)
Xianxiao Zhou (3464498)
Yuji Kajiwara (265261)
Kristen Brennand (228552)
Gabriele De Luca (244081)
John Crary (3464492)
Patrizia Casaccia (225204)
Joseph Buxbaum (3464495)
Michelle Ehrlich (3453359)
Sam Gandy (6210)
Alison Goate (48756)
Pavel Katsel (257692)
Eric Schadt (105785)
Vahram Haroutunian (23823)
Bin Zhang (64682)

November 2016

Top 10,000 probesets ranked in association with disease traits across 19 brain regions. (XLSX 6710 k...

Additional file 3: of Genetic risk for Alzheimerâs disease is concentrated in specific macrophage and microglial transcriptional networks

Katherine Tansey (4889533)
Darren Cameron (4889530)
Matthew Hill (394308)

February 2018

Table S3. Enrichment of AD-risk variants at H3K4me1 peaks from Roadmap Epigenomics Consortium data. ...

Additional file 1: of Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimerâs disease patients

Abstract

Extracted data

Additional file 1: of Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimerâs disease patients

Abstract

Extracted data

Related items

Related items

Additional file 1: of Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimerâs disease patients

Abstract

Extracted data

Additional file 1: of Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimerâs disease patients

Abstract

Extracted data

Related items

Related items

Additional file 1: of Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimerâs disease patients

Additional file 1: of Condition-specific gene co-expression network mining identifies key pathways and regulators in the brain tissue of Alzheimerâs disease patients