How, what & why publish (or perish…)

1. How, what & why publish(or perish…)

2. Outline • How to publish? • What to publish? • The rewards of publishing… 

3. 1. How to publish… • Published Online October 11 2012Science 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

8. 2. What to publish?  • Projects on the way out • Projects in the working • Future projects to discuss and prioritize

9. A. Projects finalized and on the way out: • 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).

10. B.Projects we are currently working on(order is random) • 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 (NirGonen) • Identifying SL pairs as a key for selective treatment in cancer (Livnat & Adam)

11. Projects we are currently working on(in continuation) • 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).

12. 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)

13. What next? The future around the corner

14. A. Generic computational challenges: • 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).

15. B. General basic research questions & clinically-oriented applications • 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 multiple-sclerosis, 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…

16. C. Studying cancer metabolism • 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).

17. D. Lower priority potential projects/open-comments • : • Mitochondrial disorders – (the recent NEJM review, OrlyAlpeleg). • 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)

18. 3. Online dating and the rewards of publishing  Dating in a digital world Scientific American Mind, September 2012