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TeMMPo is a Django web application that expect a file of abstracts representing the articles linking exposure to outcome. It then expects you to specify MeSH terms for the exposure, MeSH terms for candidate mechanisms and MeSH terms for outcomes. This page describes each of these in more detail.

You must create an account to use TeMMPo. TeMMPo is provided as a free-to-use service, and the user registration and login is simply used to enable you to track jobs and re-use search criteria.

The article upload page is the first link under "Search" after you have logged in to TeMMPo.

You can upload abstracts in either OVID MEDLINE® or PubMed MEDLINE® format. The following examples illustrate the required format. It is possible to exclude some fields to reduce file size, but it is essential that MeSH Subject Headings are included. At present the file upload limit is set at 1000MB.

‐ Includes "MeSH Subject Headings"

<1>
						Unique Identifier
						  23482392
						Record Owner
						  From MEDLINE, a database of the U.S. National Library of Medicine.
						Status
						  MEDLINE
						Authors
						  Li C.  Han J.  Yao Q.  Zou C.  Xu Y.  Zhang C.  Shang D.  Zhou L.  Zou C.  Sun Z.  Li J.  Zhang Y.  Yang H.  Gao X.  Li X.
						Authors Full Name
						  Li, Chunquan.  Han, Junwei.  Yao, Qianlan.  Zou, Chendan.  Xu, Yanjun.  Zhang, Chunlong.  Shang, Desi.  Zhou, Lingyun.  Zou, Chaoxia.  Sun, Zeguo.  Li, Jing.  Zhang, Yunpeng.  Yang, Haixiu.  Gao, Xu.  Li, Xia.
						Institution
						  College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, PR China.
						Title
						  Subpathway-GM: identification of metabolic subpathways via joint power of interesting genes and metabolites and their topologies within pathways.
						Source
						  Nucleic Acids Research.  41(9):e101, 2013 May.
						Other ID
						  Source: NLM. PMC3643575
						MeSH Subject Headings
						    Colorectal Neoplasms/ge [Genetics]
						    Colorectal Neoplasms/me [Metabolism]
						    Histamine/me [Metabolism]
						    Humans
						    Male
						    *Metabolic Networks and Pathways/ge [Genetics]
						    *Metabolomics
						    Neoplasm Metastasis
						    Prostatic Neoplasms/ge [Genetics]
						    Prostatic Neoplasms/me [Metabolism]
						    Prostatic Neoplasms/pa [Pathology]
						    *Transcriptome
						Abstract
						  Various 'omics' technologies, including microarrays and gas chromatography mass spectrometry, can be used to identify hundreds of interesting genes, proteins and metabolites, such as differential genes, proteins and metabolites associated with diseases. Identifying metabolic pathways has become an invaluable aid to understanding the genes and metabolites associated with studying conditions. However, the classical methods used to identify pathways fail to accurately consider joint power of interesting gene/metabolite and the key regions impacted by them within metabolic pathways. In this study, we propose a powerful analytical method referred to as Subpathway-GM for the identification of metabolic subpathways. This provides a more accurate level of pathway analysis by integrating information from genes and metabolites, and their positions and cascade regions within the given pathway. We analyzed two colorectal cancer and one metastatic prostate cancer data sets and demonstrated that Subpathway-GM was able to identify disease-relevant subpathways whose corresponding entire pathways might be ignored using classical entire pathway identification methods. Further analysis indicated that the power of a joint genes/metabolites and subpathway strategy based on their topologies may play a key role in reliably recalling disease-relevant subpathways and finding novel subpathways.
						Registry Number/Name of Substance
						  51-45-6 (Histamine).
						Publication Type
						  Journal Article.  Research Support, Non-U.S. Gov't.
						Date Created
						  20130506
						Year of Publication
						  2013
						Link to the Ovid Full Text or citation
						 http://ovidsp.ovid.com/ovidweb.cgi?T=JS&CSC=Y&NEWS=N&PAGE=fulltext&D=medl&AN=23482392
						Link to the External Link Resolver
						 http://linkserver.bristol.ac.uk:9003/prod?sid=OVID:medline&id=pmid:23482392&id=doi:10.1093%2Fnar%2Fgkt161&issn=0305-1048&isbn=&volume=41&issue=9&spage=e101&pages=e101&date=2013&title=Nucleic+Acids+Research&atitle=Subpathway-GM%3A+identification+of+metabolic+subpathways+via+joint+power+of+interesting+genes+and+metabolites+and+their+topologies+within+pathways.&aulast=Li&pid=%3Cauthor%3ELi+C%3C%2Fauthor%3E%3CAN%3E23482392%3C%2FAN%3E%3CDT%3EJournal+Article%3C%2FDT%3E

‐ Includes "MH"

PMID- 26010633
				OWN - NLM
				STAT- MEDLINE
				DA  - 20150527
				DCOM- 20150529
				LR  - 20150708
				IS  - 1538-3598 (Electronic)
				IS  - 0098-7484 (Linking)
				VI  - 313
				IP  - 20
				DP  - 2015 May 26
				TI  - Copy number variations and cognitive phenotypes in unselected populations.
				PG  - 2044-54
				LID - 10.1001/jama.2015.4845 [doi]
				AB  - IMPORTANCE: The association of copy number variations (CNVs), differing numbers
				      of copies of genetic sequence at locations in the genome, with phenotypes such as
				      intellectual disability has been almost exclusively evaluated using clinically
				      ascertained cohorts. The contribution of these genetic variants to cognitive
				      phenotypes in the general population remains unclear. OBJECTIVE: To investigate
				      the clinical features conferred by CNVs associated with known syndromes in adult
				      carriers without clinical preselection and to assess the genome-wide consequences
				      of rare CNVs (frequency </=0.05%; size >/=250 kilobase pairs [kb]) on carriers'
				      educational attainment and intellectual disability prevalence in the general
				      population. DESIGN, SETTING, AND PARTICIPANTS: The population biobank of Estonia
				      contains 52,000 participants enrolled from 2002 through 2010. General
				      practitioners examined participants and filled out a questionnaire of health- and
				      lifestyle-related questions, as well as reported diagnoses. Copy number variant
				      analysis was conducted on a random sample of 7877 individuals and
				      genotype-phenotype associations with education and disease traits were evaluated.
				      Our results were replicated on a high-functioning group of 993 Estonians and 3
				      geographically distinct populations in the United Kingdom, the United States, and
				      Italy. MAIN OUTCOMES AND MEASURES: Phenotypes of genomic disorders in the general
				      population, prevalence of autosomal CNVs, and association of these variants with
				      educational attainment (from less than primary school through scientific degree)
				      and prevalence of intellectual disability. RESULTS: Of the 7877 in the Estonian
				      cohort, we identified 56 carriers of CNVs associated with known syndromes. Their
				      phenotypes, including cognitive and psychiatric problems, epilepsy, neuropathies,
				      obesity, and congenital malformations are similar to those described for carriers
				      of identical rearrangements ascertained in clinical cohorts. A genome-wide
				      evaluation of rare autosomal CNVs (frequency, </=0.05%; >/=250 kb) identified 831
				      carriers (10.5%) of the screened general population. Eleven of 216 (5.1%)
				      carriers of a deletion of at least 250 kb (odds ratio [OR], 3.16; 95% CI,
				      1.51-5.98; P = 1.5e-03) and 6 of 102 (5.9%) carriers of a duplication of at least
				      1 Mb (OR, 3.67; 95% CI, 1.29-8.54; P = .008) had an intellectual disability
				      compared with 114 of 6819 (1.7%) in the Estonian cohort. The mean education
				      attainment was 3.81 (P = 1.06e-04) among 248 (>/=250 kb) deletion carriers and
				      3.69 (P = 5.024e-05) among 115 duplication carriers (>/=1 Mb). Of the deletion
				      carriers, 33.5% did not graduate from high school (OR, 1.48; 95% CI, 1.12-1.95; P
				      = .005) and 39.1% of duplication carriers did not graduate high school (OR, 1.89;
				      95% CI, 1.27-2.8; P = 1.6e-03). Evidence for an association between rare CNVs and
				      lower educational attainment was supported by analyses of cohorts of adults from
				      Italy and the United States and adolescents from the United Kingdom. CONCLUSIONS
				      AND RELEVANCE: Known pathogenic CNVs in unselected, but assumed to be healthy,
				      adult populations may be associated with unrecognized clinical sequelae.
				      Additionally, individually rare but collectively common intermediate-size CNVs
				      may be negatively associated with educational attainment. Replication of these
				      findings in additional population groups is warranted given the potential
				      implications of this observation for genomics research, clinical care, and public
				      health.
				FAU - Mannik, Katrin
				AU  - Mannik K
				AD  - Center for Integrative Genomics, University of Lausanne, Lausanne,
				      Switzerland2Estonian Genome Center, University of Tartu, Tartu.
				FAU - Magi, Reedik
				AU  - Magi R
				AD  - Estonian Genome Center, University of Tartu, Tartu.
				FAU - Mace, Aurelien
				AU  - Mace A
				AD  - Department of Medical Genetics, University of Lausanne, Lausanne,
				      Switzerland4Swiss Institute of Bioinformatics, Lausanne, Switzerland.
				FAU - Cole, Ben
				AU  - Cole B
				AD  - Department of Laboratory Medicine and Pathology, University of Minnesota Medical
				      School, Minneapolis.
				FAU - Guyatt, Anna L
				AU  - Guyatt AL
				AD  - Bristol Genetic Epidemiology Laboratories, School of Social and Community
				      Medicine, University of Bristol, Bristol, United Kingdom.
				FAU - Shihab, Hashem A
				AU  - Shihab HA
				AD  - Bristol Genetic Epidemiology Laboratories, School of Social and Community
				      Medicine, University of Bristol, Bristol, United Kingdom7MRC Integrative
				      Epidemiology Unit, School of Social and Community Medicine, University of
				      Bristol, Bristol, United Kingdom.
				FAU - Maillard, Anne M
				AU  - Maillard AM
				AD  - Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland.
				FAU - Alavere, Helene
				AU  - Alavere H
				AD  - Estonian Genome Center, University of Tartu, Tartu.
				FAU - Kolk, Anneli
				AU  - Kolk A
				AD  - Estonian Genome Center, University of Tartu, Tartu8Department of Neurology and
				      Neurorehabilitation, Children's Clinic, Tartu University Hospital, Tartu,
				      Estonia.
				FAU - Reigo, Anu
				AU  - Reigo A
				AD  - Estonian Genome Center, University of Tartu, Tartu.
				FAU - Mihailov, Evelin
				AU  - Mihailov E
				AD  - Estonian Genome Center, University of Tartu, Tartu.
				FAU - Leitsalu, Liis
				AU  - Leitsalu L
				AD  - Estonian Genome Center, University of Tartu, Tartu9Institute of Molecular and
				      Cell Biology, University of Tartu, Tartu, Estonia.
				FAU - Ferreira, Anne-Maud
				AU  - Ferreira AM
				AD  - Center for Integrative Genomics, University of Lausanne, Lausanne,
				      Switzerland4Swiss Institute of Bioinformatics, Lausanne, Switzerland.
				FAU - Noukas, Margit
				AU  - Noukas M
				AD  - Estonian Genome Center, University of Tartu, Tartu9Institute of Molecular and
				      Cell Biology, University of Tartu, Tartu, Estonia.
				FAU - Teumer, Alexander
				AU  - Teumer A
				AD  - Institute for Community Medicine, University Medicine Greifswald, Greifswald,
				      Germany.
				FAU - Salvi, Erika
				AU  - Salvi E
				AD  - Deparment of Health Sciences, University of Milan, Milan, Italy.
				FAU - Cusi, Daniele
				AU  - Cusi D
				AD  - Deparment of Health Sciences, University of Milan, Milan, Italy12Institute of
				      Biomedical Technologies, Italian National Research Council, Milan, Italy.
				FAU - McGue, Matt
				AU  - McGue M
				AD  - Department of Psychology, University of Minnesota, Minneapolis.
				FAU - Iacono, William G
				AU  - Iacono WG
				AD  - Department of Psychology, University of Minnesota, Minneapolis.
				FAU - Gaunt, Tom R
				AU  - Gaunt TR
				AD  - Bristol Genetic Epidemiology Laboratories, School of Social and Community
				      Medicine, University of Bristol, Bristol, United Kingdom7MRC Integrative
				      Epidemiology Unit, School of Social and Community Medicine, University of
				      Bristol, Bristol, United Kingdom.
				FAU - Beckmann, Jacques S
				AU  - Beckmann JS
				AD  - Swiss Institute of Bioinformatics, Lausanne, Switzerland.
				FAU - Jacquemont, Sebastien
				AU  - Jacquemont S
				AD  - Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland.
				FAU - Kutalik, Zoltan
				AU  - Kutalik Z
				AD  - Department of Medical Genetics, University of Lausanne, Lausanne,
				      Switzerland4Swiss Institute of Bioinformatics, Lausanne, Switzerland14Institute
				      of Social and Preventive Medicine, Lausanne University Hospital (CHUV), Lausanne,
				      Switzerland.
				FAU - Pankratz, Nathan
				AU  - Pankratz N
				AD  - Department of Laboratory Medicine and Pathology, University of Minnesota Medical
				      School, Minneapolis.
				FAU - Timpson, Nicholas
				AU  - Timpson N
				AD  - Bristol Genetic Epidemiology Laboratories, School of Social and Community
				      Medicine, University of Bristol, Bristol, United Kingdom7MRC Integrative
				      Epidemiology Unit, School of Social and Community Medicine, University of
				      Bristol, Bristol, United Kingdom.
				FAU - Metspalu, Andres
				AU  - Metspalu A
				AD  - Estonian Genome Center, University of Tartu, Tartu9Institute of Molecular and
				      Cell Biology, University of Tartu, Tartu, Estonia.
				FAU - Reymond, Alexandre
				AU  - Reymond A
				AD  - Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.
				LA  - eng
				GR  - 102433/Z/13/Z/Wellcome Trust/United Kingdom
				GR  - AA09367/AA/NIAAA NIH HHS/United States
				GR  - AA11886/AA/NIAAA NIH HHS/United States
				GR  - DA024417/DA/NIDA NIH HHS/United States
				GR  - DA05147/DA/NIDA NIH HHS/United States
				GR  - DA13240/DA/NIDA NIH HHS/United States
				GR  - MH066140/MH/NIMH NIH HHS/United States
				PT  - Journal Article
				PT  - Research Support, N.I.H., Extramural
				PT  - Research Support, Non-U.S. Gov't
				PL  - United States
				TA  - JAMA
				JT  - JAMA
				JID - 7501160
				SB  - AIM
				SB  - IM
				CIN - JAMA. 2015 May 26;313(20):2029-30. PMID: 26010630
				MH  - Adolescent
				MH  - Adult
				MH  - Cognition
				MH  - *DNA Copy Number Variations
				MH  - Educational Status
				MH  - Epilepsy/genetics
				MH  - Estonia
				MH  - Female
				MH  - Genome-Wide Association Study
				MH  - Great Britain
				MH  - *Heterozygote
				MH  - Humans
				MH  - Intellectual Disability/*genetics
				MH  - Italy
				MH  - Male
				MH  - Mental Disorders/*genetics
				MH  - Obesity/genetics
				MH  - Phenotype
				MH  - United States
				EDAT- 2015/05/27 06:00
				MHDA- 2015/05/30 06:00
				CRDT- 2015/05/27 06:00
				AID - 2297168 [pii]
				AID - 10.1001/jama.2015.4845 [doi]
				PST - ppublish
				SO  - JAMA. 2015 May 26;313(20):2044-54. doi: 10.1001/jama.2015.4845.

After uploading your abstracts you will be able to enter exposure terms. There are three options for selecting terms:

Enter terms manually (semi-colon delimited)

This can be useful for editing and reusing long lists of MeSH terms

Browse through the MeSH tree and select terms

You can choose to "explode" descendent MeSH terms with the radio buttons at the top of the list

Search the MeSH tree

This automatically expands the relevant branches, allowing you to easily find and select terms

After selecting exposures you will be able to enter mechanism terms. The same three options for selecting terms are presented:

Enter terms manually (semi-colon delimited)

This can be useful for editing and reusing long lists of MeSH terms

Browse through the MeSH tree and select terms

You can choose to "explode" descendent MeSH terms with the radio buttons at the top of the list

Search the MeSH tree

This automatically expands the relevant branches, allowing you to easily find and select terms

You can use the "breadcrumb trail" at the top to browse back to exposure selection if you wish

Finally, after entering mechanism MeSH terms you will be able to select outcome terms. There are three options for selecting terms:

Enter terms manually (semi-colon delimited)

This can be useful for editing and reusing long lists of MeSH terms

Browse through the MeSH tree and select terms

You can choose to "explode" descendent MeSH terms with the radio buttons at the top of the list

Search the MeSH tree

This automatically expands the relevant branches, allowing you to easily find and select terms

You can use the "breadcrumb trail" at the top to browse back to exposure or mechanism selection if you wish

The genes and filter section lets you enter gene names (or any text words) as potential mechanistic terms. This expands the functionality of TeMMPo to enable mechanistic terms other than MeSH terms - this is particularly relevant for terms such as gene names (which are not represented in MeSH).

An additional overall MeSH filter can also be applied in this section. This enables the user to restrict the articles used in the counting process.

Once your analysis is complete you are presented with a table of results. If this is your first analysis only one row will show. The results table contains:

  • View search criteria: allows you to see which terms were selected. This is useful for reproducibility, allowing you too view a record of the analytical parameters. In addition, you can copy and edit any of the lists and enter them into the text box on any of the MeSH selection pages
  • Visualisations: this provides a Sankey visualisation of the highest priority mechanisms (full results can be downloaded)
  • Score data: contains the full set of results as a csv file. For each mechanism the columns contain: mechanism MeSH term, number of articles linking that mechanism to exposure, number of articles linking that mechanism to outcome and priority score (see below)
  • Abstract IDs: a csv file containing the abstract IDs used in analysis.

The priority score is a weighted ratio of the number of abstracts linking the mechanisms to exposure (EM) and outcome (MO), calculated as:

score = max(EM,MO) / min(EM,MO) x (EM + MO)

Select "Search Criteria" from the results table, or selecting "Reuse existing search" from the "Search" menu enables you to reuse either a set of abstracts you have uploaded previously or a set of search criteria (or both).

Reuse search criteria will repeat a previous analysis (on the same set of abstracts), but allowing you to edit all of the MeSH terms used.

Reuse abstracts only will allow you to define an entirely new search on an existing set of articles.