27 Works

A new genus of treeshrew and other micromammals from the middle Miocene hominoid locality of Ramnagar, Udhampur District, Jammu & Kashmir, India

Ramesh Sehgal, Abhishek Singh, Christopher Gilbert, Biren Patel, Christopher Campisano, Keegan Selig, Rajeev Patnaik & Ningthoujam Premjit Singh
The fossil record of treeshrews, hedgehogs, and other micromammals from the Lower Siwaliks of India is sparse. Here, we report on a new genus and species of fossil treeshrew, specimens of the hedgehog Galerix, and other micromammals from the middle Miocene (Lower Siwalik) deposits surrounding Ramnagar (Udhampur District, Jammu & Kashmir), at a fossil locality known as Dehari. The treeshrew from Dehari (Sivatupaia ramnagarensis gen. nov. et sp. nov.) currently represents the oldest record of...

Additional file 1 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 1. Figure S1. (A) Distribution of number of metabolites each microbiome consume or produce. (B) Distribution of number of microbiomes each metabolite.

Additional file 5 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 5. Table S4. Drug screen results using Drugbank database.

Additional file 7 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 7. Table S6. Potential homolog proteins that have homologs with pathogenic microbe proteins but do not have homologs with commensal microbe proteins.

PyTorch geometric datasets for morphVQ models

Oshane Thomas, Hongyu Shen, Ryan L. Rauum, William E. H. Harcourt-Smith, John D. Polk & Mark Hasegawa-Johnson
The methods of geometric morphometrics are commonly used to quantify morphology in a broad range of biological sciences. The application of these methods to large datasets is constrained by manual landmark placement limiting the number of landmarks and introducing observer bias. To move the field forward, we need to automate morphological phenotyping in ways that capture comprehensive representations of morphological variation with minimal observer bias. Here, we present Morphological Variation Quantifier (morphVQ), a shape analysis...

Analysis of Language Change in Collaborative Instruction Following

Anna Effenberger, Eva Yan, Rhia Singh, Alane Suhr & Yoav Artzi

Additional file 10 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 10. Table S9. Background targets list used in target functional annotation analysis.

Additional file 2 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 2. Table S1. Microbes with pathogenic effects on human health by manually literature review.

Additional file 6 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 6. Table S5. Drugs that are found in both drug screen results using Drugbank database and that using STITCH database.

Additional file 9 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 9. Table S8. Background drugs list used in drug overrepresentation analysis.

Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Abstract Background Microbes are associated with many human diseases and influence drug efficacy. Small-molecule drugs may revolutionize biomedicine by fine-tuning the microbiota on the basis of individual patient microbiome signatures. However, emerging endeavors in small-molecule microbiome drug discovery continue to follow a conventional “one-drug-one-target-one-disease” process. A systematic pharmacology approach that would suppress multiple interacting pathogenic species in the microbiome, could offer an attractive alternative solution. Results We construct a disease-centric signed microbe–microbe interaction network using...

Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Abstract Background Microbes are associated with many human diseases and influence drug efficacy. Small-molecule drugs may revolutionize biomedicine by fine-tuning the microbiota on the basis of individual patient microbiome signatures. However, emerging endeavors in small-molecule microbiome drug discovery continue to follow a conventional “one-drug-one-target-one-disease” process. A systematic pharmacology approach that would suppress multiple interacting pathogenic species in the microbiome, could offer an attractive alternative solution. Results We construct a disease-centric signed microbe–microbe interaction network using...

Additional file 10 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 10. Table S9. Background targets list used in target functional annotation analysis.

Additional file 1 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 1. Figure S1. (A) Distribution of number of metabolites each microbiome consume or produce. (B) Distribution of number of microbiomes each metabolite.

Additional file 2 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 2. Table S1. Microbes with pathogenic effects on human health by manually literature review.

Additional file 4 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 4. Table S3. The Microbes with unknown effects in literature reviews and their SRWR inferred microbe effects.

Additional file 6 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 6. Table S5. Drugs that are found in both drug screen results using Drugbank database and that using STITCH database.

Additional file 7 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 7. Table S6. Potential homolog proteins that have homologs with pathogenic microbe proteins but do not have homologs with commensal microbe proteins.

Data associated with: Minor genetic consequences of a major mass mortality: Short-term effects in Pisaster ochraceus

Lauren Schiebelhut, Melina Giakoumis, Rita Castilho, Paige Duffin, Jonathan Puritz, John Wares, Gary Wessel & Michael Dawson
Mass mortality events (MMEs) are increasing globally in frequency and magnitude, largely due to human-induced change. The effects of these MMEs, both in the long- and short-term, are of imminent concern because of their ecosystem impacts. Genomic data can be used to reveal some of the population-level changes associated with MMEs. Here, we use reduced-representation sequencing to identify potential short-term genetic impacts of an MME associated with a sea star wasting (SSW) outbreak. We tested...

Additional file 8 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 8. Table S7. Drug screen results in STITCH database.

Additional file 9 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 9. Table S8. Background drugs list used in drug overrepresentation analysis.

Additional file 3 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 3. Table S2. Microbes with commensal effects on human health by manually literature review.

Additional file 5 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 5. Table S4. Drug screen results using Drugbank database.

Additional file 8 of Small molecule modulation of microbiota: a systems pharmacology perspective

Qiao Liu, Bohyun Lee & Lei Xie
Additional file 8. Table S7. Drug screen results in STITCH database.

The multi-dimensional impacts of business accelerators: what does the research tell us?

Juanita Gonzalez-Uribe &

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  • City University of New York
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  • Peking University
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  • Second Xiangya Hospital of Central South University
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