Trackademia

Welcome to Trackademia

The idea behind Trackademia is to build on existing academic databases like Google Scholar and OpenAlex so that you can trust the data and use it for whatever you want. That comes down to two things.

More data, and more ways to use it. We aggregate publication data from every major source into a single dataset and add information pulled from faculty CVs. Then we let you slice it however you want: choose which sources to build from, write your own formulas, weight journals, adjust for department size.

More accurate, and honest about where it isn’t. We focus on a smaller set of schools so we can verify everything carefully. Faculty lists come from department websites rather than being inferred from publication records, so we know who should be in the data before we go looking. When we can’t find data on someone, we record the gap instead of dropping them. Every number comes with a coverage rate you can check against ground truth.

Everything in Trackademia is built from seven units. AI merges duplicate records across sources and tags each publication so these categories hold up:

  • Publication — citation counts, authors, journal, peer review status, and more
  • Publication group — versions of the same work combined into one entity, such as a working paper and the article it became
  • Academic
  • Department
  • University
  • Field
  • Journal

There are two modes. In Database mode you browse the underlying records and filter by any of the seven units. In Analytics mode you get graphs and comparisons, and you switch views to compare two departments, compare one department against the average of the others, or see them all at once. Tabs let you focus on a particular level of the data.

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Journal

Nature Biotechnology

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Citation weight

TierA
Weight in force
Weightingoff

Weight inputs

Each figure with its percentile among the ranked journals. A is the median, over the academics with a work here, of that academic’s citations to the works this site counts for them - never a Google Scholar profile total. Over every academic of this field, all years, whatever the filters select.

A · academics’ median15,475.0 · 73%
B · citations per work742.9 · 98%
N · works48 · 46%
P · academics11 · 19%
Formula result1.232

From this institution

Under these filters. A work with no citation count is unknown here, never a zero.

Works48
Citations21,545 over 29 of 48 works
Citations per counted work742.9
Weighted citations
Academics11
Departments6
First seen1994

Works placed per year

48 of these 48 works carry a year; an undated work is in no year. Works placed, under these filters.

Departments publishing there 6

DepartmentWorks
Harvard Chemistry38
Yale Chemistry4
Princeton Chemistry3
Columbia Chemistry1
Cornell Chemistry1
Penn Chemistry1

A work held by two departments counts once in each, so these add up to more than the works above.

Works placed there 48

YearTitleAcademicsCitations
2020Genome Editing with CRISPR-Cas Nucleases, Base Editors, Transposases, and Prime EditorsDavid R. Liu2,769
2013High-Throughput Profiling of Off-Target DNA Cleavage Reveals RNA-Programmed Cas9 Nuclease SpecificityDavid R. Liu2,121
2019CRISPResso2 provides accurate and rapid genome editing sequence analysisDavid R. Liu1,940
2015Cationic Lipid-Mediated Delivery of Proteins Enables Efficient Protein-Based Genome Editing In Vitro and In VivoDavid R. Liu1,862
2014Fusion of Catalytically Inactive Cas9 to FokI Nuclease Improves the Specificity of Genome ModificationDavid R. Liu1,276
2020Phage-Assisted Evolution of an Adenine Base Editor with Enhanced Cas Domain Compatibility and ActivityDavid R. Liu1,274
2018Improving Cytidine and Adenine Base Editors by Expression Optimization and Ancestral ReconstructionDavid R. Liu1,169
2017Increasing the Genome-Targeting Scope and Precision of Base Editing with Engineered Cas9-Cytidine Deaminase FusionsDavid R. Liu1,052
2020Prime Genome Editing in Rice and WheatDavid R. Liu1,037
2022Engineered pegRNAs Improve Prime Editing EfficiencyDavid R. Liu890
2008Systems-level metabolic flux profiling identifies fatty acid synthesis as a target for antiviral therapyJoshua Rabinowitz777
2022Programmable Deletion, Replacement, Integration, and Inversion of Large DNA Sequences with Twin Prime EditingDavid R. Liu756
2020Evaluation and Minimization of Cas9-Independent Off-Target DNA Editing by Cytosine Base EditorsDavid R. Liu587
2014Enzyme clustering accelerates processing of intermediates through metabolic channelingJoshua Rabinowitz528
2007Redirecting lipoic acid ligase for cell surface protein labeling with small-molecule probesJeremy M. Baskin480
2020Continuous Evolution of SpCas9 Variants Compatible with Non-G PAMsDavid R. Liu470
2019Continuous Evolution of Base Editors with Expanded Target Compatibility and Improved ActivityDavid R. Liu459
1994Recombinant Proteins Can Be Released From E. Coli Cells By Repeated Cycles of Freezing and ThawingMichael Hecht390
2020Programmable m6A Modification of Cellular RNA with a Cas13-Directed MethyltransferaseDavid R. Liu363
2000Synthesis of positional-scanning libraries of fluorogenic peptide substrates to define the extended substrate specificity of plasmin and thrombinJon Ellman355
2019Circularly permuted and PAM-modified Cas9 variants broaden the targeting scope of base editorsDavid R. Liu351
2025Lung and liver editing by lipid nanoparticle delivery of a stable CRISPR–Cas9 ribonucleoproteinKai Chen217
2022Prediction of protein–ligand binding affinity from sequencing data with interpretable machine learningNeel H. Shah143
2023Design of a mucin-selective protease for targeted degradation of cancer-associated mucinsStacy Malaker94
2023Time-tagged ticker tapes for intracellular recordingsAdam Cohen64
2023Massively parallel knock-in engineering of human T cellsSarah Slavoff57
2011New fluorescent probes for super-resolution imagingXiaowei Zhuang39
2012Discovering ligand-receptor interactionsSarah Slavoff22
2026AI-guided Re-design of Laboratory-Evolved Reverse Transcriptases Enhances Prime Editing in Human Cells and in AnimalsDavid R. Liu3
2024Efficient Prime Editing in Mouse Brain, Liver and Heart with Dual AAVsDavid R. Liu
2026Mechanistic Machine Learning for Prediction of Prime Editing OutcomesDavid R. Liu
2026Evolution of Botulinum Neurotoxin Serotype X Proteases to Induce Inflammatory Cell Death in Cancer CellsDavid R. Liu
2025Branched, Chemically Modified Poly(A) Tails Enhance the Translation Capacity of mRNADavid R. Liu
2023High-Throughput Continuous Evolution of Compact Cas9 Variants Targeting Single-Nucleotide-Pyrimidine PAMsDavid R. Liu
2024Adenine Transversion Editors Enable Precise, Efficient A•T-To-C•G Base Editing in Mammalian Cells and EmbryosDavid R. Liu
2021Efficient C•G-to-G•C Base Editors Developed Using CRISPRi Screens, Target-Library Analysis and Machine LearningDavid R. Liu
2002Nucleic Acid Evolution and Minimization by Nonhomologous Random RecombinationDavid R. Liu
2025Directed Evolution of Engineered Virus-Like Particles with Improved Production and Transduction EfficienciesDavid R. Liu
2026Directed Evolution of Small RNA-Stabilizing Motifs that Improve Prime EditingDavid R. Liu
2023Evolution of an Adenine Base Editor into a Small, Efficient Cytosine Base Editor with Low Off-Target ActivityDavid R. Liu
2024Engineered Virus-Like Particles for Transient Delivery of Prime Editor Ribonucleoprotein Complexes In VivoDavid R. Liu
2025High Throughput Evaluation of Genetic Variants with Prime Editing Sensor LibrariesDavid R. Liu
2024Efficient Prime Editing in Two-Cell Mouse Embryos Using PEmbryoDavid R. Liu
2022CRISPR-Free Base Editors with Enhanced Activity and Expanded Targeting Scope in Mitochondrial and Nuclear DNADavid R. Liu
2026Virus-like Particles Enable Targeted Gene Engineering and Pooled CRISPR Screening in Primary Human Myeloid CellsDavid R. Liu
2019CRISPResso2: Accurate and Rapid Analysis of Genome Editing Data from Nucleases and Base EditorsDavid R. Liu
2024A Prime Editor Mouse to Model a Broad Spectrum of Somatic Mutations In VivoDavid R. Liu
2019Circularly Permuted and Modified-PAM Base Editors with Diversified Targeting ScopeDavid R. Liu

Citations as counted, before any journal weight: 29 of these 48 works carry a count, and a work with no count is unknown, never a zero.