How, what & why publish
(or perish…)
Outline
1. How to publish?
1. What to publish?
2. The rewards of publishing… 
1. How to publish…
Published Online October 11 2012 •
Science 23 November 2012:
Vol. 338 no. 6110 pp. 1065-1069
DOI: 10.1126/science.1227833
Report •
Flows of Research Manuscripts Among •
Scientific Journals Reveal Hidden Submission
Patterns
V. Calcagno et al
Fig. 1 The network of scientific journals as derived from manuscript submission flows.
V Calcagno et al. Science 2012;338:1065-1069
Published by AAAS
Fig. 2 Journal impact structures resubmission patterns.
V Calcagno et al. Science 2012;338:1065-1069
Published by AAAS
Fig. 3 High-impact journals publish proportionally fewer first-intent articles.
V Calcagno et al. Science 2012;338:1065-1069
Published by AAAS
Fig. 4 Submission history affects citation counts.
V Calcagno et al. Science 2012;338:1065-1069
Published by AAAS
2. What to publish? 
• Projects on the way out
• Projects in the working
• Future projects to discuss and prioritize
A. Projects finalized and on the way out:
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MTA & Aging (Keren)
PRIME (Keren)
TOX (Allon)
SUMEX (Matt & Raphy)
Homeo (Noa & Allon)
NAFLD (Livnat)
Second FH project (Livnat)
Proliferation signatures in cancer and normal cells
(Yedael).
B. Projects we are currently working on
(order is random)
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Modeling SNP effects in metabolism - Alik and Keren.
Studying Breast cancer metabolism across multiple omics levels
(Livnat).
A large-scale study predicting metabolic symptoms in diseases and
metabolic drugs side-effects – (Itay & Keren)
Minenv and growing unculturable organisms (Matt & Raphy);
Promiscuity and antibiotic resistance; (Matt & Raphy)
Studying statin effects and predicting other anti-cholesterol drugs
(Osher & Keren).
Gut microbiome & glycans project (Omer & Raphy).
SNP signatures and co-morbidity (Yedael)
Metabolism in AD (Shiri)
Metabolism in Epilepsy (Nir Gonen)
Identifying SL pairs as a key for selective treatment in cancer (Livnat &
Adam)
Projects we are currently working on
(in continuation)
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A new approach for integrating expression data in metabolic modeling
(Adam)
The mechanisms behind and the oncogenic role of inverted IDH flux in
breast cancer (Livnat)
Identification of `true' bacterial growth media (Oren)
Selective enhancement of ROS production in cancer (Erez)
Studying the Warburg effect across the NCI60 cell-lines (Keren)
Involvement of TLM genes (human orthologs) in diseases (Yedael)
Plant metabolism; better models of Arabidopsis and corn; improved
yield… (Yoav & Raphy)
Brain metabolic evolution (Gal Chechik and his students)
Functional alignment of metabolic spaces across species (Arnon &
Roded).
C. Projects on hold:
• Tuvik's three layered network robustness project
(?)..
• Csaba's ROS / antibiotics project (Keren)
• The plasma metabolic network project (awaiting
Helsinki approval)
D. Administrative tasks:
• Lab code repository;
• Microme deliverables (Alik & Ariel)
What next? The future around the
corner
A. Generic computational challenges:
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Utilizing widespread inferred network activation data to orient (provide direction
to) reactions in the human model (Keren, Appnedix D)
Go thermodynamics and biomarkers (Elad, Yoav, Keren, Allon).
Extending MTA to over expression; (Keren)
Finding exchange media - inferring human physiol media at different tissues critical for model building – the antibiotics for sepsis bacteria - using it later for
inferring biomarkers of disease from expression data; (Keren)
Building tissue models – estimation tissue specific: a. objective functions (the
BOSS algorithm), b. media, and c. bounds, orienting reactions (Keren)
Simulating multi-tissue metabolism; validation via increased fit to proteomics and
biomarkers data..
Using GSMMs to constrain the hypotheses space of gene association testing –
use imat to find best fit of metab state to data; then rank genes in accordance with
confidence interval’s
Utilizing stochiometric couplings to better interpret metabolomic data
measurements (Appendix C).
Using essentiality data to infer the metabolic state (Livnat (?))
Enriching and solving metabolic models with integrated vitamin metabolism
(with focus on humans, of course).
B. General basic research questions & clinically-oriented applications
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Metabolic alterations and tissue salvage after stroke or myocardial infarction
Using TOX to predict the toxicity of activating drug candidates in proliferating cells (Allon).
Extending MTA to identify metabolic gene targets of drugs (Appendix B) – (Keren).
Antibodies against metabolic enzymes and autoimmune disorders (-For example, in multiplesclerosis, there is an autoimmune response that harms the fatty myelin that surrounds the neurons;
Livnat/Matej)
obesity – white/brown adipose tissue; MTA reversal
Different `good' and `bad' ways to slow metabolism… slower metab in aging, but animals with
slow metab have longer life spans; is increased BMR required to counteract greater errors in
proteins etc?
Use MTA for comprehensive drug repurposing for metabolic disorders.
Generating a databases of tissue-specific biomarkers that can point to tissues specifically afflicted
in a specific disease.
In silico evolution of existing organisms.. (?!) – take a few extant bacterial species, construct their
common ancestors back in the tree, and then use the latter to try and evolve back the extant
ones?! Allow gene addition/deletion, learn about likely objective functions and metabolic
environments.
Identify alterations in the production of key metabolites that serve as signaling molecules…
Same re. the production of neurotransmitters – after identifying potential targets – examine their
down regulation in disease gene expression data and test/validate vs co-mborbidity data!
The relation between the extent of drugs' side-effects and the level in which they cause a
deviation from the healthy or disease tissues states…
C. Studying cancer metabolism
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MTA in cancer - reversing the Warburg effect (Keren).
The metab of the naked mole rat vs the mouse/rat – Church's 2011 plos one
paper;
Estimate the fitness of adapted resistant cancers after anti cancer metab
treatment.. use these estimates to compute optimal treatment strategies for
keeping cancer in check..
Identify drugs targets that can selectively inhibit estrogen production in Breast
cancer (Livnat)
Studying the metab alterations behind emerging resistance in cancer cells Studying alterations in key metabolites modulating the main signaling pathways
considered to be central in cancer; including Proliferative signaling, Energy
metabolism & Growth suppressors
Inducing autophagy as treatment in cancer and in neurodegenration (the science
review by Josh Rabinovitz).
Metabolic signatures of advanced tumors
Metabolic factors that determine tissue targets of metastases (Livnat).
D. Lower priority potential projects/open-comments
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Mitochondrial disorders – (the recent NEJM review, Orly Alpeleg).
Systems biology of nutrition – answering basic questions on the relations between metabolic subsystems
and more (See Appendix A).
Restoring dopamine metabolism in Parkinson (see recent posting in ideas dir); app. SN cells are most
sensitive to energy shortage?
http://www.plosone.org/article/info:doi/10.1371/journal.pone.0002444
Cancer proteomics - the idea that during cancer progression there may be a change in the composition
and production of essential amino acids; ideas re. the Savaguah rules (Appendix C).
The metabolic state in Progeria (?)
The merging of bacterial and archeon metabolism (question posed by Uri)?
Characterize cell-cycle metab behavior.
Metformin and the risk of cancer… - http://www.sciencemag.org/content/335/6064/28.full
The s.aures project that Allon and Ori have started.. Barbasi's strains models;..
Augmentation of certain anticancer treatments by NSAIDs..
* The yeast/human gene complementarities project;
The 2010 MSB paper from the Church lab on a bacteria specializing on cellulose degradation.
The buffering/longevity idea (1.2012, Keren – what happened with it?)
The definitive imat..: The idea is to perform an iterative search for a threshold that maximizes the over
all imat fitness score..
- A further related idea is to score reactions by their global effect on determining the activity of other
reactions in the network given typical expression data..
Survey of gene transplant in humans; Predict life improving genes in humans… (Allon)
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3. Online dating and the rewards of
publishing 
Dating in a digital world
Scientific American Mind, September 2012